Sample records for heavy precipitation simulation

Precipitation scavenging can effectively remove particulates from the atmosphere. Therefore, this process is of importance in the real-time modeling of atmospheric transport for hazardous materials. To account for the rainfall effect in LLNL operational dispersion model, a modified version of a standard below-cloud aerosol scavenging model has been developed to handle the emergency response in this scenario (Loosmore and Cerdewall, 2003, hereafter referred to as LC). Two types of rain data can be used to incorporate precipitation scavenging in the dispersion model; realtime measurements (rain gauge and radar), and model prediction. The former approach has been adopted in LC's study for the below-cloud scavenging problem based on the surface rain measurements. However, the in-cloud scavenging effect remains unresolved as a restriction of available real-time measurements in providing the vertical structure of precipitation systems. The objective of this study is to explore the possibility to incorporate three-dimensional precipitation structure of forecast data into the dispersion model. Therefore, both in-cloud and below-cloud scavenging effects can be included in LLNL aerosol scavenging model. To this end, a mesoscale model (Naval Research Laboratory 3-D weather forecast model, COAMPS) is used to demonstrate this application using a mid-west severe storm case occurring on July 18, 1997.

Reliable climate-change projections of extreme precipitation events are of great interest to decision makers, due to potentially important hydrological impacts such as floods, land slides and debris flows. Low-resolution climate models generally project increases of heavyprecipitation events with climate change, but there are large uncertainties related to the limited spatial resolution and the parameterized representation of atmospheric convection. Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Comparison between 12 and 2km resolutions with parameterized and explicit convection, respectively, reveals close agreement in terms of mean summer precipitation amounts (decrease by 30%), and regarding slight increases of heavy day-long events (amounting to 15% for 90th-percentile for wet-day precipitation). However, the different resolutions yield large differences regarding extreme hourly precipitation, with the 2km version projecting substantially faster increases of heavy hourly precipitation events (about 30% increases for 90th-percentile hourly events). Ban, N., J. Schmidli and C. Sch

Changes in the characteristics of daily precipitation in response to global warming may have serious impacts on human life and property. An analysis of precipitation in climate models is performed to evaluate how well the models simulate the present climate and how precipitation may change in the future. Models participating in phase 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) have substantial biases in their simulation of heavyprecipitation intensity over parts of North America during the 20th century. Despite these biases, the large-scale atmospheric circulation accompanying heavyprecipitation is either simulated realistically or the strength of the circulation is overestimated. The biases are not related to the large-scale flow in a simple way, pointing toward the importance of other model deficiencies, such as coarse horizontal resolution and convective parameterizations, for the accurate simulation of intense precipitation. Although the models may not sufficiently simulate the intensity of precipitation, their realistic portrayal of the large-scale circulation suggests that projections of future precipitation may be reliable. In the CMIP5 ensemble, the distribution of daily precipitation is projected to undergo substantial changes in response to future atmospheric warming. The regional distribution of these changes was investigated, revealing that dry days and days with heavy-extreme precipitation are projected to increase at the expense of light-moderate precipitation over much of the middle and low latitudes. Such projections have serious implications for future impacts from flood and drought events. In other places, changes in the daily precipitation distribution are characterized by a shift toward either wetter or drier conditions in the future, with heavy-extreme precipitation projected to increase in all but the driest subtropical subsidence regions. Further analysis shows that increases in heavyprecipitation in midlatitudes

Twenty years of regional climate simulated by the Weather Research and Forecasting model for North America has been analyzed to study the influence of the atmospheric rivers and the role of the land surface on heavyprecipitation and flooding in the western U.S. Compared to observations, the simulation realistically captured the 95th percentile extreme precipitation, mean precipitation intensity, as well as the mean precipitation and temperature anomalies of all the atmospheric river events between 1980-1999. Contrasting the 1986 President Day and 1997 New Year Day atmospheric river events, differences in atmospheric stability are found to have an influence on the spatial distribution of precipitation in the Coastal Range of northern California. Although both cases yield similar amounts of heavyprecipitation, the 1997 case was found to produce more runoff compared to the 1986 case. Antecedent soil moisture, the ratio of snowfall to total precipitation (which depends on temperature), and existing snowpack all seem to play a role, leading to a higher runoff to precipitation ratio simulated for the 1997 case. This study underscores the importance of characterizing or simulating atmospheric rivers and the land surface conditions for predicting floods, and for assessing the potential impacts of climate change on heavyprecipitation and flooding in the western U.S.

Accurate prediction of precipitation is one of the most difficult and significant tasks in weather forecasting. Heavyprecipitations in the Korean Peninsula are caused by various physical mechanisms, which are affected by shortwave trough, quasi-stationary moisture convergence zone among varying air masses, and a direct/indirect effect of tropical cyclone. Many previous studies have used observations, numerical modeling, and statistics to investigate the potential causes of warm-season heavyprecipitation in South Korea. Especially, the frequency of warm-season torrential rainfall events more than 30 mm/h precipitation has increased threefold in Seoul, a metropolitan city in South Korea, in recent 30 years. Localized heavy rainfall events in South Korea generally arise from mesoscale convective systems embedded in these synoptic scale disturbances along the Changma front, or from convective instabilities resulting from unstable air masses. In order to investigate localized heavyprecipitation system in Seoul metropolitan area, analysis and numerical experiment were performed for a typical event in 20 June 2014. This case is described to a structure of baroclinic instability associated with a short-wave trough from the northwest and high moist and warm air by a thermal low from the southwest of the Korean Peninsula. We investigated localized heavyprecipitation in narrow zone of the Seoul urban area using numerical simulations based on the Weather Research and Forecast (WRF) model with convective scale. The topography and land use data of the revised U.S. Geological Survey (USGS) data and the appropriate set of physical scheme options for WRF model simulation were deliberated. Simulation experiments showed patches of primary physical structures related to the localized heavyprecipitation using the diagnostic fields, which are storm relative helicity (SRH), updraft helicity (UH), and instantaneous contraction rates (ICON). SRH and UH are dominantly related to

Several heavyprecipitation episodes occurred over Taiwan from August 10 to 13, 1994. Precipitation patterns and characteristics are quite different between the precipitation events that occurred from August 10 and I I and from August 12 and 13. In Part I (Chen et al. 2001), the environmental situation and precipitation characteristics are analyzed using the EC/TOGA data, ground-based radar data, surface rainfall patterns, surface wind data, and upper air soundings. In this study (Part II), the Penn State/NCAR Mesoscale Model (MM5) is used to study the precipitation characteristics of these heavyprecipitation events. Various physical processes (schemes) developed at NASA Goddard Space Flight Center (i.e., cloud microphysics scheme, radiative transfer model, and land-soil-vegetation surface model) have recently implemented into the MM5. These physical packages are described in the paper, Two way interactive nested grids are used with horizontal resolutions of 45, 15 and 5 km. The model results indicated that Cloud physics, land surface and radiation processes generally do not change the location (horizontal distribution) of heavyprecipitation. The Goddard 3-class ice scheme produced more rainfall than the 2-class scheme. The Goddard multi-broad-band radiative transfer model reduced precipitation compared to a one-broad band (emissivity) radiation model. The Goddard land-soil-vegetation surface model also reduce the rainfall compared to a simple surface model in which the surface temperature is computed from a Surface energy budget following the "force-re store" method. However, model runs including all Goddard physical processes enhanced precipitation significantly for both cases. The results from these runs are in better agreement with observations. Despite improved simulations using different physical schemes, there are still some deficiencies in the model simulations. Some potential problems are discussed. Sensitivity tests (removing either terrain or radiative

The research program was initiated with the objective of evaluating a new process, the sulfide precipitation of heavy metals from industrial wastewaters. The process was expected to effect a more complete removal of heavy metals than conventional lime processing because of the mu...

Analysis of heavyprecipitation events in Lithuania is presented in this work. Research was divided into two parts. Spatial distribution and dynamic of heavyprecipitation events in Lithuania during observation period (1961-2008) is presented in the first part and climate predictions for XXI century according to outputs of CCLM model are in the second. Daily data from 17 meteorological stations were used for the analysis of heavyprecipitation events in Lithuania. Research covers period from 1961 to 2008. Annual and seasonal heavyprecipitation values and the recurrence of extreme daily and 3-day precipitation events were analyzed. Spatial distribution of heavyprecipitation events in Lithuania was determined; the trends of such precipitation recurrence were identified. Also, daily and 3-day annual maxima probabilities were calculated using the Generalized Extreme Value (GEV) distribution. 10, 30 and 100 years return period was analyzed. Finally, atmospheric circulation processes during heavyprecipitation events were described using the adapted Hess & Brezowski macrocirculation form classification Predictions of changes of heavyprecipitation recurrence in Lithuania are also presented in this study. Output data of the regional climate model CCLM (COSMO - Climate Limited-area Model) for the period 1971-2100 were used. Predictions were based on A1B and B1 emission scenarios. Despite of relatively small area and quite negligible differences in altitude there are significant unevenness in spatial distribution of heavyprecipitation events in Lithuania. The mean annual number of cases when daily precipitation amount exceeded 10 mm fluctuates from 12.4 to 21.9 and from 5.3 to 10.5 when 3-day precipitation exceeded 20 mm. The probability of maximum precipitation amount for 10 year return period appears very familiar to spatial distribution of heavyprecipitation recurrence: the highest values can be expected in the western part (55-60 mm daily and 75-85 mm in 3-days

An intercomparison of eight different microphysics parameterization schemes available in the Weather Research and Forecasting (WRF) model and an analysis of the sensitivity of predicted precipitation to horizontal resolution are presented in this paper. Three different case studies, corresponding to severe rainfall events occurred over the Liguria region (Italy) between October 2010 and November 2011, have been considered. In all the selected cases, the formation of a quasi-stationary mesoscale convective system over the Ligurian Sea interacting with local dynamical effects (orographically-induced low-level wind and temperature gradients) played a crucial role in the generation of severe precipitations. The data set used to evaluate model performances has been extracted from the official regional network, composed of about 150 professional WMO-compliant stations. Two different strategies have been exploited to assess the model skill in forecasting precipitation: a traditional approach, where forecasts and observations are matched on a point-by-point basis, and an object-based method where model success is based on the correct localization and intensity of precipitation patterns. This last method overcomes the known fictitious models performance degradation for increasing spatial resolution. As remarkable results of this analysis, a clear role of horizontal resolution on the model performances accompanied by the identification of a set of best-performing parameterization schemes emerge. The outcomes presented here offer important suggestions for operational weather prediction systems under potentially dangerous heavyprecipitations triggered by the mechanisms discussed throughout the paper.

Heavyprecipitation cause devastating warm-season floods and cool-season snow and icing hazards that impact socio-economic communities of various scales. The frequency and severity of extreme precipitation events potentially are likely to be impacted by climate change. In this study we will investigate potential change in extreme precipitation intensity in a future climate over the Colorado headwaters region based on an extreme value approach ("peak-over-threshold" approach). The data come from Weather Research and Forecasting (WRF) model simulations of current and future climate conducted by the Colorado Headwaters Project (e.g., Rasmussen et al. 2011). The simulations were performed over eight years with 4, 12, and 36 km horizontal grid spacing. In the current study, we first evaluate the model ability to properly represent extreme precipitation events from the current climate simulation. Then we present changes in extreme precipitation intensity in the future climate for different seasons and over eight mountain ranges of the Colorado headwaters region. Our analyses so far have shown that the 4-km model outperformed coarser grid resolution models in representing extreme precipitation compared to Snowpack Telemetry (SNOTEL) surface observations. Overall, the 10-year return level in the future climate increased (more intense extreme precipitation) for all mountain ranges in the cool season. There was a general decrease in the 10-year return level (less intense extreme precipitation) in the warm season. The sign and magnitude of the change shows regional differences possibly related to seasonal storm tracks and characteristics. Detailed analysis from case studies will be presented to illustrate the impacts of a warmer and moister atmosphere on the microphysical structure of storm clouds and surface precipitation distribution.

Heavy rainfall occurred over the western side of Taiwan's complex terrain from August 10 to 13, 1994 after Typhoon Doug moved northward from the East China Sea into Taiwan and on towards the Yellow Sea. On August 10, most of the rainfall fell over sloped areas. The heaviest daily rainfall totals were in excess of 200 mm over southwestern as well as central Taiwan. However, not much rainfall occurred over northern Taiwan. The lack of rainfall over northern Taiwan also occurred on August 11, 12 and 13. The larger rainfall amounts shifted westward from the sloped areas on August 10 toward lower terrain on August 11. On August 12 and 13, most of the higher rainfall amounts were found over the coastal area in southwestern Taiwan. Notably, about 300 to 400 mm per day fell over the coastal area in southwest Taiwan on August 12 and 13. The distribution of rainfall amount was different on August 10 and 11 (termed as Case 1) compared to August 12 and 13 (termed as Case 2). The environmental situation and precipitation characteristics are analyzed using EC/TOGA data, ground-based radar data, surface rainfall patterns, surface wind data, and upper air soundings. Chen at al. (2001) also categorized the precipitation pattern into two types, propagating and quasi-stationary. For the propagating type of precipitation, rainrates increased or remained the same as systems went from the plains to mountainous regions. With the quasi-stationary type of precipitation, however, rainrates decreased as precipitation propagated across the plains and into the mountains. The focus of this study is to understand what causes the h1aher amounts of rainfall over Taiwan, and what factors influence where the higher amounts of rainfall will occur, over sloped areas or over coastal areas.

Strong Bora and Sirocco winds over the Adriatic Sea favour intense air-sea interactions and are often associated with heavy rainfall that affects the mountainous areas surrounding the basin. A convection-permitting model (MOLOCH) has been implemented at high resolution (2 km) in order to analyse several precipitation events over northern Italy, occurred during different seasons of the year and presenting different rainfall characteristics (stratiform, convective, orographic), and to possibly identify the relevant physical mechanisms involved. With the aim of assessing the impact of the sea surface temperature (SST) and surface fluxes on the intensity and location of the rainfall, sensitivity experiments have been performed taking into account the possible variability of SST analysis for model initialization. The model has been validated and specific diagnostic tools have been developed and applied to evaluate the vertically integrated moisture fluxes feeding the precipitating system or to compute a water balance in the atmosphere over the sea. The results show that the Adriatic Sea plays a role in determining the boundary layer characteristics through exchange of heat and moisture thus modifying the low-level flow dynamics and its interaction with the orography. This in turn impacts on the rainfall. Although the results vary among the analysed events, the precise definition of the SST and its evolution can be relevant for accurate precipitation forecasting.

In this study, the Weather Research and Forecasting (WRF) model version 3.2 is used to examine the impact of precipitating ice and especially snow-graupel partitioning in the simulation of a heavy rainfall event over Chalkidiki peninsula in Northern Greece. This major precipitation event, associated with a case of cyclogenesis over the Aegean Sea, occurred on the 8th of October 2006 causing severe flooding and damage. Two widely used microphysical parameterizations, the Purdue Lin (PLIN) and WRF Single-Moment 6-class scheme (WSM6) are compared with available raingauge measurements over the complex topography of Chalkidiki. To further investigate the importance of snow and graupel relative mass content and the treatment of precipitating ice sedimentation velocity, two older versions of the WSM6 scheme were compiled and run with the current model. The verification results indicate that all simulations were found to match raingauge data more closely over the eastern mountainous Chalkidiki peninsula where maximum accumulations were observed. In other stations all schemes overestimate 24h accumulated rainfall except a station situated at the western part of the peninsula, where none of the simulations was able to reproduce observed rainfall. Graupel dominance in PLIN generates rapid precipitation fallout at the point of maximum predicted 24h accumulation. Similar behavior is shown in WSM6 from WRF version 2, but with significant less rainfall. Increasing snow amounts aloft, due to the unified treatment of precipitating ice in WSM6 from WRF version 3, modifies rain dynamics which decrease rainfall rates, but increases 24h accumulations. A sensitivity experiment where PLIN is used with snow accretion by graupel turned off, indicated that this process seems to be the most important factor controlling the differences in surface precipitation between PLIN and WSM6 from WRF version 3, determining the spatial and temporal distribution of this heavyprecipitation event. The

Heavyprecipitation events in the Alpine region often cause floods, rock-falls and mud slides with severe consequences for population and economy. Breaking synoptic Rossby waves located over western Europe, play a central role in triggering such heavy rain events in southern Switzerland (e.g. Massacand et al. 1998). In contrast, synoptic scale structures triggering heavyprecipitation on the north side of the Swiss Alps and orographic effects have so far not been studied comprehensively. An observation based high resolution precipitation data set for Switzerland and the Alps (MeteoSwiss) is used to identify heavyprecipitation events affecting the north side of the Swiss Alps for the time period 1961-2010. For these events a detailed statistical and dynamical analysis of the upper level flow is conducted using ECMWFs ERA-40 and ERA-Interim reanalysis data sets. For the analysis north side of the Swiss Alps is divided in two investigation areas north-eastern and western Switzerland following the Swiss climate change scenarios (Bey et al. 2011). A subjective classification of upper level structures triggering heavyprecipitation events in the areas of interest is presented. Four classes are defined based on the orientation and formation of the dynamical tropopause during extreme events in the northern part of Switzerland and its sub-regions. The analysis is extended by a climatology of breaking waves and cut-offs following the method of Wernli and Sprenger (2007) to examine their presence and location during extreme events. References Bey I., Croci-Maspoli M., Fuhrer J., Kull C, Appenzeller C., Knutti R. and Schär C. Swiss Climate Change Scenarios CH2011, C2SM, MeteoSwiss, ETH, NCCR Climate, OcCC (2011), http://dx.doi.org/10.3929/ethz-a-006720559 Massacand A., H. Wernli, and H.C. Davies, 1998. Heavyprecipitation on the Alpine South side: An upper-level precursor. Geophys. Res. Lett., 25, 1435-1438. MeteoSwiss 2011. Documentation of Meteoswiss grid-data products

Heavyprecipitation events, associated with winter storm systems, frequently produce devastating flooding throughout the state of California. One of the most disastrous floods in recent years occurred in March of 1995. A storm moved through California from March 7 to 11, 1995 causing flooding in a total of 57 counties in California. the storm moved to the northwest coast of California on March 7 and started producing heavy rainfall on March 8 in northern California. Then the storm moved southward and continuously produced heavy rain as it moved through California. On March 9, a maximum of 177 mm precipitation fell in northern California and brought a maximum of 140 mm precipitation to that area on March 10. In addition to the heavy rain, heavy snow fell in the higher elevations, with snow depths exceeding 12 meters in some locations in the Sierra Nevada mountains, reported by late March. Although such storms have been a research subject for many years, some features of the California storms, such as slow movement, the mesoscale structure and orographic effects on the storm movement and structure are not well understood. Consequently, storms such as the March 1995 event, are often not well predicted. The purpose of this study is to try to improve our understanding of the underlying physical mechanisms that produce the mesoscale structure and storm movement throughout the state. A greater understanding of the physical interactions un these storms will ultimately lead to improved precipitation forecasts, including both the spatial and temporal distribution. Improved forecasts benefit society by reducing threat to life and property and to improved water resource management. We have chosen the Navy Operational Regional Atmospheric Prediction System (NORAPS) to simulate the storms and study the dynamics and physics of these storm systems.

Very short-term precipitation forecasting (i.e nowcasting) systems may provide valuable support in the weather surveillance process as they allow to issue automated early warnings for heavyprecipitation events (HPE) as reviewed recently by Pierce et al. (2012). The need for warnings is essential in densely populated regions of small catchments, such as those typically found in Mediterranean coastal areas, prone to flash-floods. Several HPEs that occurred in NE Spain are analyzed using a nowcasting system based on the extrapolation of rainfall fields observed with weather radar following a Lagrangian approach developed and tested successfully in previous studies (Berenguer et al. 2005, 2011). Radar-based nowcasts, with lead times up to 3 h, are verified here against quality-controlled weather radar quantitative precipitation estimates and also against a dense network of raingauges. The basic questions studied are the dependence of forecast quality with lead time and rainfall amounts in several high-impact HPEs such as the 7 September 2005 Llobregat Delta river tornado outbreak (Bech et al. 2007) or the 2 November 2008 supercell tornadic thunderstorms (Bech et al. 2011) - both cases had intense rainfall rates (30' amounts exceeding 38.2 and 12.3 mm respectively) and daily values above 100 mm. Verification scores indicated that forecasts of 30' precipitation amounts provided useful guidance for lead times up to 60' for moderate intensities (up to 1 mm in 30') and up to 2.5h for lower rates (above 0.1 mm). On the other hand correlations of radar estimates and forecasts exceeded Eulerian persistence of precipitation estimates for lead times of 1.5 h for moderate intensities (up to 0.8 mm/h). We complete the analysis with a discussion on the reliability of threshold to lead time dependence based on the event-to-event variability found. This work has been done in the framework of the ProFEWS project (CGL2010-15892). References Bech J, N Pineda, T Rigo, M Aran, J Amaro, M

Climate models project that heavyprecipitation events intensify with climate change. It is generally accepted that extreme day-long events will increase at a rate of about 6-7% per degree warming, consistent with the Clausius-Clapeyron relation. However, recent studies suggest that sub-daily (e.g. hourly) precipitation extremes may increase at about twice this rate (referred to as super-adiabatic scaling). Conventional climate models are not suited to assess such events, due to the limited spatial resolution and the need to parameterize convective precipitation (i.e. thunderstorms and rain showers). Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with environmental temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Consistent with previous results, projections reveal a significant decrease of mean summer precipitation (by 30%). However, unlike previous studies, we find that increase in both extreme day-long and hour-long precipitation events asymptotically intensify with the Clausius-Clapeyron relation in 2km simulation (Ban et al. 2015). Differences to previous studies might be due to the model or region considered, but we also show that

Stochastic daily precipitation models are commonly used to generate scenarios of climate variability or change on a daily time scale. The standard models consist of two components describing the occurrence and intensity series, respectively. Binary logistic regression is used to fit the occurrence data, and the intensity series is modeled by a continuous-valued right-skewed distribution, such as gamma, Weibull or lognormal. The precipitation series is then modeled using the joint density and standard software for generalized linear models can be used to perform the computations. A drawback of these precipitation models is that they do not produce a sufficiently heavy upper tail for the distribution of daily precipitation amounts; they tend to underestimate the frequency of large storms. In this study we adapted the approach of Furrer and Katz (2008) based on hybrid distributions in order to correct for this shortcoming. In particular we applied hybrid gamma - generalized Pareto (GP) and hybrid Weibull-GP distributions to develop a stochastic precipitation model for daily rainfall at Ihtiman in western Bulgaria. We report the results of simulations designed to compare the models based on the hybrid distributions and those based on the standard distributions. Some potential difficulties are outlined.

Stochastic daily precipitation models are commonly used to generate scenarios of climate variability or change on a daily timescale. The standard models consist of two components describing the occurrence and intensity series, respectively. Binary logistic regression is used to fit the occurrence data, and the intensity series is modeled using a continuous-valued right-skewed distribution, such as gamma, Weibull or lognormal. The precipitation series is then modeled using the joint density, and standard software for generalized linear models can be used to perform the computations. A drawback of these precipitation models is that they do not produce a sufficiently heavy upper tail for the distribution of daily precipitation amounts; they tend to underestimate the frequency of large storms. In this study, we adapted the approach of Furrer and Katz (2008) based on hybrid distributions in order to correct for this shortcoming. In particular, we applied hybrid gamma-generalized Pareto (GP) and hybrid Weibull-GP distributions to develop a stochastic precipitation model for daily rainfall at Ihtiman in western Bulgaria. We report the results of simulations designed to compare the models based on the hybrid distributions and those based on the standard distributions. Some potential difficulties are outlined.

The primary aim of this study is to understand the heavyprecipitation events over Oceanic regions using vector wind retrievals from space based scatterometers in combination with precipitation products from satellite and model reanalysis products. Heavyprecipitation over oceans is a less understood phenomenon and this study tries to fill in the gaps which may lead us to a better understanding of heavyprecipitation over oceans. Various phenomenon may lead to intense precipitation viz. MJO (Madden-Julian Oscillation), Extratropical cyclones, MCSs (Mesoscale Convective Systems), that occur inside or outside the tropics and if we can decipher the physical mechanisms behind occurrence of heavyprecipitation, then it may lead us to a better understanding of such events which further may help us in building more robust weather and climate models. During a heavyprecipitation event, scatterometer wind observations may lead us to understand the governing dynamics behind that event near the surface. We hypothesize that scatterometer winds can observe significant changes in the near-surface circulation and that there are global relationships among these quantities. To the degree to which this hypothesis fails, we will learn about the regional behavior of heavyprecipitation-producing systems over the ocean. We use a "precipitation feature" (PF) approach to enable statistical analysis of a large database of raining features.

Heavyprecipitation events are of interest to weather forecasters, local government officials, and the Department of Defense. These events can cause flooding which endangers lives and property. Military concerns include decreased trafficability for military vehicles, which hinders both war- and peace-time missions. Even in data-rich areas such as the United States, it is difficult to determine when and where a heavyprecipitation event will occur. The challenges are compounded in data-denied regions. The hypothesis that total precipitable water anomaly (TPWA) will be positive and increasing preceding heavyprecipitation events is tested in order to establish an understanding of TPWA evolution. Results are then used to create a precipitation forecast aid. The operational, 16 km-gridded, 6-hourly TPWA product developed at the Cooperative Institute for Research in the Atmosphere (CIRA) compares a blended TPW product with a TPW climatology to give a percent of normal TPWA value. TPWA evolution is examined for 84 heavyprecipitation events which occurred between August 2010 and November 2011. An algorithm which uses various TPWA thresholds derived from the 84 events is then developed and tested using dichotomous contingency table verification statistics to determine the extent to which satellite-based TPWA might be used to aid in forecasting precipitation over mesoscale domains. The hypothesis of positive and increasing TPWA preceding heavyprecipitation events is supported by the analysis. Event-average TPWA rises for 36 hours and peaks at 154% of normal at the event time. The average precipitation event detected by the forecast algorithm is not of sufficient magnitude to be termed a "heavy" precipitation event; however, the algorithm adds skill to a climatological precipitation forecast. Probability of detection is low and false alarm ratios are large, thus qualifying the algorithm's current use as an aid rather than a deterministic forecast tool. The algorithm

Since precipitation can be distributed very unequally during heavy rains, the hydrological response can be significantly influenced not only by the precipitation amount but also by the spatial and temporal distribution of the rainfall. The latter one seems to be more important in case of very small catchments. Therefore, not only design precipitation totals but also knowledge on intensity variations during the precipitation episodes is needed to design the runoff. The suggested methodology is based on the analysis of the maximum precipitation intensities in step-by-step shortened time windows. Individual episodes are labeled by a series of parameters representing the precipitation concentration and intensity increase or decrease. The methodology was applied to adjusted radar-derived precipitation estimates from the Czech Republic 2002-2011. We present results from selected pixels with different topography. The application proved significant differences in precipitation intensity course between lowlands and mountains but also among episodes of various durations.

1.Introduction Combined with summer heavy rainfall and urbanization today's urban area face higher frequency of heavy rainfall with higher intensity in summer than before. Heavy rainfall in short time makes it low elevation area to be susceptible to more flooding than before. According to KMA it is announced as heavy rainfall warning whose precipitation amount is equal to or greater than 150mm per 12 hours. And sometimes, these rainfall events bring out severe disasters such as the case of flooding in Gangnam Station, Daechi Station and landslides which resulted in 20 person death in downtown Seoul on July 27th, 2011. Thus, the purpose of this study is to investigate the spatial and temporal pattern of heavyprecipitation in Seoul. Ultimately it aims to contribute these results to the proper urban planning and management. 2. Materials and Methods In this study, the digital topograhic data and weather data in Seoul Metropolitan Area were used to figure out the spatial distribution of summer heavy rainfall. The precipitation data in summer (June to Sep.) season were used to detect the recent changes of temporal and spatial features from 1995 to 2014 (20 years) using Automatic Weather tation (AWS) data in Seoul Metropolitan Area. The precipitation amount in summer during the past 20 years has been on the rise but rainy days have barely changed，which reveals the daily precipitation intensity has increased. After deriving the characteristic of heavy rainfall, the relationship among precipitation, topography and land uses were interpreted and discussed. This study is to investigate the characteristics of flood prone area by focusing topographic and land use characteristics. Ultimately it contributes to prepare the guideline for flood preventive urban plannig.

the size of the region is linked with a built-in test on regional homogeneity of data. Once a pooling group is delineated, weights based on a dissimilarity measure are assigned to individual sites involved in a pooling group, and all (weighted) data are employed in the estimation of model parameters and high quantiles at a given location. The ROI method is compared with the Hosking-Wallis (HW) regional frequency analysis, which is based on delineating fixed regions (instead of flexible pooling groups) and assigning unit weights to all sites in a region. The comparison of the performance of the individual regional models makes use of data on annual maxima of 1-day precipitation amounts at 209 stations covering the Czech Republic, with altitudes ranging from 150 to 1490 m a.s.l. We conclude that the ROI methodology is superior to the HW analysis, particularly for very high quantiles (100-yr return values). Another advantage of the ROI approach is that subjective decisions - unavoidable when fixed regions in the HW analysis are formed - may efficiently be suppressed, and almost all settings of the ROI method may be justified by results of the simulation experiments. The differences between (any) regional method and single-site analysis are very pronounced and suggest that the at-site estimation is highly unreliable. The ROI method is then applied to estimate high quantiles of precipitation amounts at individual sites. The estimates and their uncertainty are compared with those from a single-site analysis. We focus on the eastern part of the Czech Republic, i.e. an area with complex orography and a particularly pronounced role of Mediterranean cyclones in producing precipitation extremes. The design values are compared with precipitation amounts recorded during the recent heavyprecipitation events, including the one associated with the flash flood on June 24, 2009. We also show that the ROI methodology may easily be transferred to the analysis of precipitation extremes

Trends in monthly heavyprecipitation, defined by a return period of one year, are assessed for statistical significance in observations and Global Climate Model (GCM) simulations over the contiguous United States using Monte Carlo non-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall's {tau} test, implying the robustness of the approach. Two different observational data-sets are employed to test for trends in monthly heavyprecipitation and are found to exhibit consistent results. Both data-sets demonstrate upward trends, one of which is found to be statistically significant at the 95% confidence level. Upward trends similar to observations are observed in some climate model simulations of the twentieth century, but their statistical significance is marginal. For projections of the twenty-first century, a statistically significant upwards trend is observed in most of the climate models analyzed. The change in the simulatedprecipitation variance appears to be more important in the twenty-first century projections than changes in the mean precipitation. Stochastic fluctuations of the climate-system are found to be dominate monthly heavyprecipitation as some GCM simulations show a downwards trend even in the twenty-first century projections when the greenhouse gas forcings are strong.

Picked-up ion precipitations are a potential mechanism to increase an atmospheric escape from the unmagnetized planet of Mars. The interplanetary magnetic field (IMF) embedded in the supersonic solar wind is one of the crucial parameters to control the behavior of the Martian planetary heavy ions. We statistically investigated the effects of the IMF orientation on planetary heavy ions precipitating toward the Martian ionosphere by using data obtained from the Ion Mass Analyzer (IMA) onboard the Mars Express (MEX). To compensate for the absence of a magnetometer onboard MEX, we estimated the IMF orientation from the velocity distribution function of exospheric protons observed in the solar wind. The statistical analysis shows that the precipitations of planetary heavy ions tend to be observed in the direction or the anti-parallel direction of the solar wind electric field inferred from the estimated IMF orientation. We defined the IMF polarity for one event via comparisons of the ion velocity distribution function obtained from MEX/IMA observations and a statistical trajectory tracing of test particles. The estimated polarity corresponds to the anti-parallel direction to the solar wind electric field and is consistent with the asymmetrical distribution of planetary heavy ion precipitation in terms of the solar wind electric field derived from the previous numerical simulations. The observed precipitating planetary heavy ions are accelerated only up to a few keV. This feature may reflect the short distance from the picked-up region in the magnetosheath.

As Savannah River Site (SRS) personnel have studied methods of preparing high-level waste for vitrification in the Defense Waste Processing Facility (DWPF), questions have arisen with regard to the formation of insoluble waste precipitates at inopportune times. One option for decontamination of the SRS waste streams employs the use of an engineered form of crystalline silicotitanate (CST). Testing of the process during FY 1999 identified problems associated with the formation of precipitates during cesium sorption tests using CST. These precipitates may, under some circumstances, obstruct the pores of the CST particles and, hence, interfere with the sorption process. In addition, earlier results from the DWPF recycle stream compatibility testing have shown that leaching occurs from the CST when it is stored at 80 C in a high-pH environment. Evidence was established that some level of components of the CST, such as silica, was leached from the CST. This report describes the results of equilibrium modeling and precipitation studies associated with the overall stability of the waste streams, CST component leaching, and the presence of minor components in the waste streams.

the size of the region is linked with a built-in test on regional homogeneity of data. Once a pooling group is delineated, weights based on a dissimilarity measure are assigned to individual sites involved in a pooling group, and all (weighted) data are employed in the estimation of model parameters and high quantiles at a given location. The ROI method is compared with the Hosking-Wallis (HW) regional frequency analysis, which is based on delineating fixed regions (instead of flexible pooling groups) and assigning unit weights to all sites in a region. The comparison of the performance of the individual regional models makes use of data on annual maxima of 1-day precipitation amounts at 209 stations covering the Czech Republic, with altitudes ranging from 150 to 1490 m a.s.l. We conclude that the ROI methodology is superior to the HW analysis, particularly for very high quantiles (100-yr return values). Another advantage of the ROI approach is that subjective decisions - unavoidable when fixed regions in the HW analysis are formed - may efficiently be suppressed, and almost all settings of the ROI method may be justified by results of the simulation experiments. The differences between (any) regional method and single-site analysis are very pronounced and suggest that the at-site estimation is highly unreliable. The ROI method is then applied to estimate high quantiles of precipitation amounts at individual sites. The estimates and their uncertainty are compared with those from a single-site analysis. We focus on the eastern part of the Czech Republic, i.e. an area with complex orography and a particularly pronounced role of Mediterranean cyclones in producing precipitation extremes. The design values are compared with precipitation amounts recorded during the recent heavyprecipitation events, including the one associated with the flash flood on June 24, 2009. We also show that the ROI methodology may easily be transferred to the analysis of precipitation extremes

Long-term changes of the frequency of heavyprecipitation occurrence along the east coast of the Indochina Peninsula were analyzed using daily data from six Vietnamese meteorological stations for the period September--November of 1961--2010. The heavyprecipitation days were defined by the 50 and 100 mm/day threshold values. The frequency of the coastal heavyprecipitation days were decomposed into tropical cyclone (TC)-induced heavyprecipitation days and non-TC heavyprecipitation days, and their contribution to recent increase in the coastal precipitation was examined. Over the 50-yr period, heavyprecipitation occurrence indices show a significant increasing trend that is linked to an increasing trend in seasonal amount of the coastal precipitation. A rapid increase in the coastal heavyprecipitation days was found from the 1990s through the 2000s. This marked increase is basically due to non-TC heavyprecipitation events, suggesting that TC passages do not play a role in the recent increase in the seasonal precipitation amount and the heavyprecipitation events. A role of tropical synoptic-scale disturbances (TSDs) as non-developing disturbances for TC formation in the non-TC heavyprecipitation events was also explored. About 70% of the non-TC heavyprecipitation events are associated with TSDs originated from the western North Pacific--South China Sea region. TSD passages are responsible for the recent increase in non-TC heavyprecipitation events.

Downscaling precipitation is a difficult challenge for the climate community. We propose and study a new stochastic weather typing approach to perform such a task. In addition to providing accurate small and medium precipitation, our procedure possesses built-in features that allow us to model adequately extreme precipitation distributions. First, we propose a new distribution for local precipitation via a probability mixture model of Gamma and Generalized Pareto (GP) distributions. The latter one stems from Extreme Value Theory (EVT). The performance of this mixture is tested on real and simulated data, and also compared to classical rainfall densities. Then our downscaling method, extending the recently developed nonhomogeneous stochastic weather typing approach, is presented. It can be summarized as a three-step program. First, regional weather precipitation patterns are constructed through a hierarchical ascending clustering method. Second, daily transitions among our precipitation patterns are represented by a nonhomogeneous Markov model influenced by large-scale atmospheric variables like NCEP reanalyses. Third, conditionally on these regional patterns, precipitation occurrence and intensity distributions are modeled as statistical mixtures. Precipitation amplitudes are assumed to follow our mixture of Gamma and GP densities. The proposed downscaling approach is applied to 37 weather stations in Illinois and compared to various possible parameterizations and to a direct modeling. Model selection procedures show that choosing one GP distribution shape parameter per pattern for all stations provides the best rainfall representation amongst all tested models. This work highlights the importance of EVT distributions to improve the modeling and downscaling of local extreme precipitations.

This study compares three different methods to evaluate the ability of Atmosphere Ocean General Circulation Models (AOGCMs) to simulateprecipitation. Currently, AOGCMs are the most powerful tool to investigate the future climate but how to evaluate them is a relatively new research field. Thus, no standardized metric for defining a climate model's skill has been defined so far. The common way to proceed is to evaluate the model simulations against observations using statistical measures. However, precipitation is highly variable on both the spatial and temporal scales. We therefore suspect that metrics representing regional features of the modelled precipitation response to climate change are more suitable to identify the good models than statistical measures defined on a global scale. Here, we compare three different ways of ranking the climate models: a) biases in a broad range of climate variables, b) only biases in global precipitation and c) regional features of modelled precipitation in areas where future changes are expected to be pronounced. Surprisingly, the multimodel mean performs only average for the feature-based ranking, while it outperforms all single models in the two bias-based rankings. In the feature-based ranking, the models performing best can be different for each region or zonal band considered and identifying them each time newly depending on the purpose may allow for more reliable projections. Further, this study reveals that many models have similar biases and that the observation datasets are often located at one end of the model range. Our results suggest that weighting the models according to their ability to simulate the present climate might lead to more reliable projections than the "one model, one vote" approach that has been favored so far.

Floods pose multi-dimensional hazards to critical infrastructure and society and these hazards may increase under climate change. While flood conditions are dependent on catchment type and soil conditions, seasonal precipitation extremes also play an important role. The extreme precipitation events driving flood occurrence may arrive non-uniformly in time. In addition, their seasonal and inter-annual patterns may also cause sequences of several events and enhance likely flood responses. Spatial and temporal patterns of extreme daily precipitation occurrence are characterized across the UK. Extreme and very heavy daily precipitation is not uniformly distributed throughout the year, but exhibits spatial differences, arising from the relative proximity to the North Atlantic Ocean or North Sea. Periods of weeks or months are identified during which extreme daily precipitation occurrences are most likely to occur, with some regions of the UK displaying multimodal seasonality. A Generalized Additive Model is employed to simulate extreme daily precipitation occurrences over the UK from 1901 to 2010 and to allow robust statistical testing of temporal changes in the seasonal distribution. Simulations show that seasonality has the strongest correlation with intra-annual variations in extreme event occurrence, while Sea Surface Temperature (SST) and Mean Sea Level Pressure (MSLP) have the strongest correlation with inter-annual variations. The north and west of the UK are dominated by MSLP in the mid-North Atlantic and the south and east are dominated by local SST. All regions now have a higher likelihood of autumnal extreme daily precipitation than earlier in the twentieth century. This equates to extreme daily precipitation occurring earlier in the autumn in the north and west, and later in the autumn in the south and east. The change in timing is accompanied by increases in the probability of extreme daily precipitation occurrences during the autumn, and in the number of

Auc(bstract) Gridded daily precipitation observations over the contiguous USA are used to investigate the past observed changes in the frequency and magnitude of heavyprecipitation, and to examine its seasonality. Analyses are based on the Climate Prediction Center (CPC) daily precipitation data from 1948 to 2012. We use a block maxima approach to identify changes in the magnitude of heavyprecipitation and a peak-over-threshold (POT) approach for the changes in the frequency. The results of this study show that there is a stronger signal of change in the frequency rather than in the magnitude of heavyprecipitation events. Also, results show an increasing trend in the frequency of heavyprecipitation over large areas of the contiguous USA with the most notable exception of the US Northwest. These results indicate that over the last 65 years, the stronger storms are not getting stronger, but a larger number of heavyprecipitation events have been observed. The annual maximum precipitation and annual frequency of heavyprecipitation reveal a marked seasonality over the contiguous USA. However, we could not find any evidence suggesting shifting in the seasonality of annual maximum precipitation by investigating whether the day of the year at which the maximum precipitation occurs has changed over time. Furthermore, we examine whether the year-to-year variations in the frequency and magnitude of heavyprecipitation can be explained in terms of climate variability driven by the influence of the Atlantic and Pacific Oceans. Our findings indicate that the climate variability of both the Atlantic and Pacific Oceans can exert a large control on the precipitation frequency and magnitude over the contiguous USA. Also, the results indicate that part of the spatial and temporal features of the relationship between climate variability and heavyprecipitation magnitude and frequency can be described by one or more of the climate indices considered here.

The phase diagram of the carbon-hydrogen system is of great importance to planetary sciences, as hydrocarbons comprise a significant part of icy giant planets and are involved in reduced carbon-oxygen-hydrogen fluid in the deep Earth. Here we use resistively- and laser-heated diamond anvil cells to measure methane melting and chemical reactivity up to 80 GPa and 2,000 K. We show that methane melts congruently below 40 GPa. Hydrogen and elementary carbon appear at temperatures of >1,200 K, whereas heavier alkanes and unsaturated hydrocarbons (>24 GPa) form in melts of >1,500 K. The phase composition of carbon-hydrogen fluid evolves towards heavy hydrocarbons at pressures and temperatures representative of Earth's lower mantle. We argue that reduced mantle fluids precipitate diamond upon re-equilibration to lighter species in the upwelling mantle. Likewise, our findings suggest that geophysical models of Uranus and Neptune require reassessment because chemical reactivity of planetary ices is underestimated. PMID:24026399

Observed intensification of precipitation extremes, responsible for extensive societal impacts, are widely attributed to anthropogenic sources, which may include indirect effects of agricultural irrigation. However quantifying the effects of irrigation on far-downstream climate remains a challenge. We use three paired Community Earth System Model simulations to assess mechanisms of irrigation-induced precipitation trends and extremes in the conterminous US and the effect on the terrestrial carbon sink. Results suggest precipitation enhancement in the central US reduced drought conditions and increased regional carbon uptake, while further downstream, the heaviest precipitation events were more frequent and intense. Specifically, moisture advection from irrigation in the western U.S. and recycling of enhanced local convective precipitation produced very-heavy storm events that were 11% more intense and occurred 23% more frequently in the densely populated greater New York City region. PMID:26642049

Observed intensification of precipitation extremes, responsible for extensive societal impacts, are widely attributed to anthropogenic sources, which may include indirect effects of agricultural irrigation. However quantifying the effects of irrigation on far-downstream climate remains a challenge. We use three paired Community Earth System Model simulations to assess mechanisms of irrigation-induced precipitation trends and extremes in the conterminous US and the effect on the terrestrial carbon sink. Results suggest precipitation enhancement in the central US reduced drought conditions and increased regional carbon uptake, while further downstream, the heaviest precipitation events were more frequent and intense. Specifically, moisture advection from irrigation in the western U.S. and recycling of enhanced local convective precipitation produced very-heavy storm events that were 11% more intense and occurred 23% more frequently in the densely populated greater New York City region. PMID:26642049

The present-day precipitation climatology of Tasmania, Australia, has been simulated for January and July using a limited area model with multiple nesting down to a resolution of 60 km. The results are superior to simulations at lower resolutions, although the high-resolution model produces excessive precipitation in regions of steep orography. A preliminary precipitation climatology is constructed for 2 x CO2 conditions from the results of the simulations for January and July. In the simulations, climate change causes precipitation to decrease over Tasmania during January, while it is increased during July. Examination of daily precipitation frequency indicates that precipitation events in January becomes less intense, but those in July become more intense. The changes in precipitation are related to modifications to the low-level synoptic fields. Some strengthening of low-level winds as a result of climate change is also noted for July.

The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products using different precipitation computation recipes, is comprehensively evaluated using statistical and hydrological methods in a usually-neglected area (northeastern China), and a framework quantifying uncertainty contributions of precipitation products, hydrological models and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products include TRMM3B42, TRMM3B42RT, GLDAS/Noah, APHRODITE, PERSIANN and GSMAP-MVK+. Two hydrological models of different complexities, i.e., a water and energy budget-based distributed hydrological model and a physically-based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and the cloud motion vectors used by GSMAP-MVK+ show huge advantage. These findings could be very useful for validation, refinement and future development of satellite-based products (e.g., NASA Global Precipitation Measurement). Although significant uncertainty exists in heavyprecipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models contribute significantly to uncertainty in discharge simulations and a better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based product, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and

Changes in intensity and frequency of daily heavyprecipitation and hot temperature extremes are analyzed in Swiss observations for the years 1901-2014/2015. A spatial pooling of temperature and precipitation stations is applied to analyze the emergence of trends. Over 90% of the series show increases in heavyprecipitation intensity, expressed as annual maximum daily precipitation (mean change: +10.4% 100 years-1; 31% significant, p < 0.05) and in heavyprecipitation frequency, expressed as the number of events greater than the 99th percentile of daily precipitation (mean change: +26.5% 100 years-1; 35% significant, p < 0.05). The intensity of heavyprecipitation increases on average by 7.7% K-1 smoothed Swiss annual mean temperature, a value close to the Clausius-Clapeyron scaling. The hottest day and week of the year have warmed by 1.6 K to 2.3 K depending on the region, while the Swiss annual mean temperature increased by 1.9 K. The frequency of very hot days exceeding the 99th percentile of daily maximum temperature has more than tripled. Despite considerable local internal variability, increasing trends in heavyprecipitation and hot temperature extremes are now found at most Swiss stations. The identified trends are unlikely to be random and are consistent with climate model projections, with theoretical understanding of a human-induced change in the energy budget and water cycle and with detection and attribution studies of extremes on larger scales.

Despite the progress in forecasting mesoscale phenomena during the recent years, the distribution and intensity of heavy convective precipitation still pose a serious challenge to models and forecasters alike. The difficulties are even greater in the presence of complex orography and in maritime regions, where upstream conditions are not well known due to a lack of observations over the sea. Both of these conditions apply to the island of Corsica. In order to study the influence of an orographic obstacle on air flows and precipitation, we present a detailed case study of a localized heavyprecipitation event of October 23 2012. The analysis is supported by observations, which were made during SOP 1 of the HyMeX (Hydrological Cycle of the Mediterranean, http://www.hymex.org/) project and in the frame of the CORSiCA observatory (http://www.obs-mip.fr/corsica). In addition, we present high resolution simulations of the event done with the Meso-NH model, to explore the capability of the model to capture the complex interaction between large scale flows and local phenomena such as flow splitting, orographic lift, and convective cells. The role of certain orographic features is tested by means of sensitivity tests with modified terrain. The localized character of the event of October 23 makes it an ideal candidate to investigate the interaction between multiple scales. While the large scale forcing was provided by a cut-off low around 60 km northeast of Menorca, the damage on Corsica was restricted to only a few towns in the south, where serious flooding occurred. Using simulation results and observations, we show that the event of 23 October 2012 was the result of flow splitting around Corsica interacting with the large scale mid and upper level wind. While the flow splitting supported convergence over the south of the island and was responsible for the stationarity of the convective system, the individual cells moved along with the mid and upper level winds. Using

A rainfall simulator, developed on the principle of droplet formation from needle tips, is described. The simulator is designed for laboratory experimentation to examine the effects of acidic precipitation on terrestrial plants. The system offers sufficient flexibility to simulat...

In the past few decades, Great Beijing area has experienced rapid and widespread urbanization, which has significantly modified the land surface physical characteristics and affects urban regional climate.A single layer urban canopy module has been developed based on the Community Land Surface Model Urban Module (CLMU) with improvements: the energy balances on the five surface conditions are considered separately: building roof, sun side and shaded side wall, pervious and impervious land surface. A method to calculate sky view factor is developed based on the physically process while most urban models simply provide an empirical value. This method improves the solar and long wave radiation simulation on each surface; a new scheme for calculating the latent heat flux is applied on both wall and impervious land; the anthropogenic heat is considered in terms of industrial production, domestic wastes, vehicles and air condition. The urban effect on summer convective precipitation under the unstable atmospheric condition over Beijing was investigated by simulating a heavy storm event in July 21st 2012. In this storm, precipitation of averagely 164 mm was brought to Beijing within 6 hours, which is the record of past 60 years in the region. Numerical simulating experiment was set up by coupling Weather Research and Forecast (WRF)/SSiB3 model with the Modified CLMU (MCLMU). Several control cases without MCLMU were set up. The horizontal resolution in the inner domains was set to be 2 km. While all of the control results drastically underestimate the urban precipitation, the result of WRF/SSiB3/MCLMU is much closer to the observation. Sensitive experiments show that the existence of large area of impervious surfaces restrain the surface evaporation and latent heat flux in urban while the anthropogenic heat and enhanced sensible heat flux warm up the lower atmospheric layer and strengthen the vertical stratification instability, which is the key factor for storm while

We investigated the performance of a convection-permitting regional climate model with respect to precipitation in the present climate around the southwestern oceanic region of Japan. The effects of explicit representation of convective processes without cumulus parameterization can be properly estimated by using a model domain without complex topography or convoluted coastlines. The amounts of annual and monthly precipitation and the frequencies of daily and hourly precipitation were well reproduced by the convection-permitting model with a 2-km grid spacing, and its performance was better than that of a model with a coarser mesh. In particular, the frequencies of hourly precipitation in the convection-permitting simulation matched the observed frequencies for precipitation intensities below 20 mm h-1. Above intensities of 20 mm h-1, however, the convection-permitting model tended to overestimate the frequency of hourly precipitation. To explore the mechanism of this overestimation of heavy hourly precipitation, the sensitivity of the frequency distribution of precipitation to the horizontal resolution was tested by changing the horizontal grid spacing of the model from 2 to 4 km and then 1.5 km. The results showed that the overestimation was increased when the horizontal resolution was coarser, owing to spurious grid-scale precipitation, which causes heavyprecipitation to be highly concentrated in a single grid. This spurious grid-scale precipitation may be caused by insufficient representation of convective downdrafts in convection-permitting simulations by models with coarser resolutions.

We analyze and intercompare the performance of a set of ten regional climate models (RCMs) along with the ensemble mean of their statistics in simulating daily precipitation characteristics during the West African monsoon (WAM) period (June-July-August-September). The experiments are conducted within the framework of the COordinated Regional Downscaling Experiments for the African domain. We find that the RCMs exhibit substantial differences that are associated with a wide range of estimates of higher-order statistics, such as intensity, frequency, and daily extremes mostly driven by the convective scheme employed. For instance, a number of the RCMs simulate a similar number of wet days compared to observations but greater rainfall intensity, especially in oceanic regions adjacent to the Guinea Highlands because of a larger number of heavyprecipitation events. Other models exhibit a higher wet-day frequency but much lower rainfall intensity over West Africa due to the occurrence of less frequent heavy rainfall events. This indicates the existence of large uncertainties related to the simulation of daily rainfall characteristics by the RCMs. The ensemble mean of the indices substantially improves the RCMs' simulated frequency and intensity of precipitation events, moderately outperforms that of the 95th percentile, and provides mixed benefits for the dry and wet spells. Although the ensemble mean improved results cannot be generalized, such an approach produces encouraging results and can help, to some extent, to improve the robustness of the response of the WAM daily precipitation to the anthropogenic greenhouse gas warming.

The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavyprecipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A

Two heavyprecipitation events that affected the north-eastern part of Romania are here described in terms of meteorological analysis. Synoptic and mesoscale conditions associated with these events are representative of a class of phenomena that produce important effects on the urban and extra-urban areas from this part of the country as a consequence of floods and flash floods. Analyses of these regional meteorological processes that generate flash floods are one of the objectives of the HYDRATE project. Romanian territory is affected by the presence of the Mediterranean Lows that transport moist and warm air from Mediterranean Sea basin. In certain meteorological conditions the Mediterranean Lows moving to East of Europe, get a retrograde movement on the Black Sea and in this way they contribute to the moisture increasing content of the forming convective systems. The retrograded Mediterranean Lows affect primary the north-eastern part of the Romania. Additionally, different mesoscale forcing mechanisms acts to continuously generate convective cells and focus the deep convection over the same region during several hours incrising in this way the flash flood potential. Heavyprecipitation events selected for analyses occurred, first of it, on 18-19 August 2005, and the second on the 23-26 July 2008, and resulted in floods and flash floods conducive to human fatalities and important economic and social damages. ECMWF model analysis was used to investigate dynamical forcing and mesoscale numerical simulation using ALADIN model was performed to investigate the mechanism responsible for the convection development. Data from conventional weather station, radar and satellite imagery were used to assess the magnitude of the rain events and to investigate the role of the different mode of convective system organization to the flash floods generation.

Understanding long-term changes in daily precipitation characteristics, particularly those associated with extreme events, is an important component of climate change science and impact assessment. Estimates of such changes are required at local scales where impacts are most keenly felt. However, the limited spatial resolution of General Circulation Models (GCMs) makes direct estimates of future daily precipitation unrealistic. A popular downscaling approach is to use GCMs to drive high-resolution Regional Climate Models (RCMs). Whilst able to simulateprecipitation characteristics at smaller scales, RCMs do not represent local variables and remain limited by systematic errors and biases. It is possible to apply statistical corrections, known as Model Output Statistics (MOS), to RCM-simulatedprecipitation. The simplest form of MOS (including bias correction) follows a 'distribution-wise' approach in which the statistical link is derived between long-term distributions of simulated and observed variables. However, more sophisticated MOS methods may be performed 'event-wise' using, for example, multiple linear regression to derive links between simulated and observed sequences of day-to-day weather. This approach requires a fitting period in which the simulated temporal evolution of large-scale weather states matches that of the real world and is thus limited to either reanalysis-driven RCMs or nudged GCM simulations. It is unclear to what extent MOS can be used to correct daily precipitation directly from GCMs, thus removing the computationally challenging RCM step from the downscaling process. Here, we present and cross-validate a stochastic, event-wise MOS method for both GCM- and RCM-simulatedprecipitation. A 'mixture' model, combining gamma and generalised Pareto distributions, is used to represent the complete (extreme and non-extreme) precipitation distribution. This is combined with a vector generalised linear model (VGLM) in order to estimate the

The description and operation of a novel cyclic electrowinning/precipitation (CEP) system for the simultaneous removal of mixtures of heavy metals from aqueous solutions are presented. CEP combines the advantages of electrowinning in a spouted particulate electrode (SPE) with that of chemical precipitation and redissolution, to remove heavy metals at low concentrations as solid metal deposits on particulate cathode particles without exporting toxic metal precipitate sludges from the process. The overall result is very large volume reduction of the heavy metal contaminants as a solid metal deposit on particles that can either be safely discarded as such, or further processed to recover particular metals. The performance of this system is demonstrated with data on the removal of mixtures of copper, nickel, and cadmium from aqueous solutions. PMID:22102792

The description and operation of a novel cyclic electrowinning/precipitation (CEP) system for the simultaneous removal of mixtures of heavy metals from aqueous solutions are presented. CEP combines the advantages of electrowinning in a spouted particulate electrode (SPE) with that of chemical precipitation and redissolution, to remove heavy metals at low concentrations as solid metal deposits on particulate cathode particles without exporting toxic metal precipitate sludges from the process. The overall result is very large volume reduction of the heavy metal contaminants as a solid metal deposit on particles that can either be safely discarded as such, or further processed to recover particular metals. The performance of this system is demonstrated with data on the removal of mixtures of copper, nickel, and cadmium from aqueous solutions. PMID:22102792

To evaluate the influence of urban non-uniformity on precipitation, the area of a city was divided into three categories (commercial, high-density residential, and low-density residential) according to the building density data from Landsat satellites. Numerical simulations of three corresponding scenarios (urban non-uniformity, urban uniformity, and non-urban) were performed in Nanjing using the WRF model. The results demonstrate that the existence of the city results in more precipitation, and that urban heterogeneity enhances this phenomenon. For the urban non-uniformity, uniformity, and non-urban experiments, the mean cumulative summer precipitation was 423.09 mm, 407.40 mm, and 389.67 mm, respectively. Urban non-uniformity has a significant effect on the amount of heavy rainfall in summer. The cumulative precipitation from heavy rain in the summer for the three numerical experiments was 278.2 mm, 250.6 mm, and 236.5 mm, respectively. In the nonuniformity experiments, the amount of precipitation between 1500 and 2200 (LST) increased significantly. Furthermore, the adoption of urban non-uniformity into the WRF model could improve the numerical simulation of summer rain and its daily variation.

The sources of sub-Saharan precipitation are studied using diagnostic procedures integrated into the code of the GISS climate model. Water vapor evaporating from defined source regions is 'tagged', allowing the determination of the relative contributions of each evaporative source to the simulated July rainfall in the Sahel. Two June-July simulations are studied to compare the moisture sources, moisture convergence patterns and the spatial variations of precipitation for rainy and drought conditions. Results for this case study indicate that patterns of moisture convergence and divergence over northern Africa had a stronger influence on model rainfall over the sub-Sahara than did evaporation rates over the adjacent oceans or moisture advection from ocean to continent. While local continental evaporation contributed significant amounts of water to Sahelian precipitation in the'rainy' simulation, moisture from the Indian Ocean did not precipitate over the Sahel in either case.

Separating urine from wastewater at the source reduces the costs of extensive wastewater treatment. Recovering the nutrients from urine and reusing them for agricultural purposes adds resource saving to the benefits. Phosphate can be recovered in the form of struvite (magnesium ammonium phosphate). In this paper, the behaviour of pharmaceuticals and heavy metals during the precipitation of struvite in urine is studied. When precipitating struvite in urine spiked with hormones and non-ionic, acidic and basic pharmaceuticals, the hormones and pharmaceuticals remain in solution for more than 98%. For heavy metals, initial experiments were performed to study metal solubility in urine. Solubility is shown to be affected by the chemical conditions of stored and therefore hydrolysed urine. Thermodynamic modelling reveals low or very low equilibrium solute concentrations for cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni) and lead (Pb). Experiments confirmed Cd, Cu and Pb carbonate and hydroxide precipitation upon metal addition in stored urine with a reaction half-life of ca. 7 days. For all metals considered, the maximum specific metal concentrations per gram phosphate or nitrogen showed to be typically several orders of magnitudes lower in urine than in commercially available fertilizers and manure. Heavy metals in struvite precipitated from normal stored urine could not be detected. Phosphate recovery from urine over struvite precipitation is shown to render a product free from most organic micropollutants and containing only a fraction of the already low amounts of heavy metals in urine. PMID:17368503

Auto regressive integrated moving average (ARIMA) models have been widely used to calculate monthly time series data formed by interannual variations of monthly data or inter-monthly variation. However, the influence brought about by inter-monthly variations within each year is often ignored. An improved ARIMA model is developed in this study accounting for both the interannual and inter-monthly variation. In the present approach, clustering analysis is performed first to hydrologic variable time series. The characteristics of each class are then extracted and the correlation between the hydrologic variable quantity to be predicted and characteristic quantities constructed by linear regression analysis. ARIMA models are built for predicting these characteristics of each class and the hydrologic variable monthly values of year of interest are finally predicted using the modeled values of corresponding characteristics from ARIMA model and the linear regression model. A case study is conducted to predict the monthly precipitation at the Lanzhou precipitation station in Lanzhou, China, using the model, and the results show that the accuracy of the improved model is significantly higher than the seasonal model, with the mean residual achieving 9.41 mm and the forecast accuracy increasing by 21%.

The climatology of a limited sample of heavyprecipitation events occurring in New Jersey, USA, is studied via statistical averaging and frequency histograms of environmental conditions at the event location. Also, the spatial distribution of related circulation features is examined. In addition, statistical differences between conditions accompanying the heavy (HEAVY) and a selected sample of light (LIGHT) precipitation events is determined. A large number of surface, standard level, stability and wind shear variables are employed as well as synoptic-scale circulation features. Variables that are identified as statistically significant, after a Student's t-test is applied to a sample mean and standard deviation are listed by season. In addition, scatter plot and composite maps are produced to illustrate conditions concurrent with the onset of heavyprecipitation.In general, there are only slight differences between values obtained for the HEAVY sample and the LIGHT sample. However, the differences are large enough for some variables in some seasons that the forecaster may be able to use these results to advantage. In particular: (i) a significantly warmer and moister atmosphere at selected levels is indicated for the HEAVY sample for Autumn and Winter but not for Spring and Summer; (ii) upper-tropospheric divergence is significantly greater in all seasons except Summer; and (iii) wind shear is significantly larger in all seasons except Summer.There is much similarity in the mean position of examined synoptic features such as troughs, vorticity maxima, jet axes and jet streaks for the two samples. However, the amplitude of circulation in the troposphere is much larger for the HEAVY sample, especially in the lower troposphere. In addition, the 850-hPa wind maximum axis (low-level jet indication) is much more often oriented from south to north and located within 300 km of the event location for the HEAVY cases. There was surprisingly no significant sample difference

We analyze the ability of the NARCCAP ensemble of regional climate models to simulate extreme monthly precipitation and its supporting circulation for regions of North America, comparing 18 years of simulations driven by the NCEP-DOE reanalysis with observations. Analysis focuses the wettest 10% of months during the cold half of the year (October-March), when we assume that resolved synoptic circulation governs precipitation. For a coastal California region, the models replicate well the monthly frequency of extremes, the amount of extreme precipitation and the 500 hPa circulation anomaly associated with the extremes. For an Upper Mississippi River Basin region, the models agree with observations in both monthly frequency and magnitude, though not as closely as for coastal California. In addition, simulated circulation anomalies for extreme months are similar to those in observations. Model success appears to result in part from the substantial seasonal variation of extremes, which the models capture well.

The proximity of the Pacific Ocean to the Transverse and Peninsular Mountain Ranges of coastal Southern California may lead to significant, orographically-enhanced precipitation in the region. With abundant moisture, such as evidenced in Pineapple Express events or atmospheric rivers, this precipitation may lead to other hydrologic hazards as flash flooding, landslides or debris flows. Available precipitation observation networks are relatively sparse in the mountainous regions and often do not capture the spatial variation of these events with high resolution. This study aims to simulate the topographically-driven precipitation over Southern California with high spatial resolution using a simplified orographic precipitation model. The model employs potential theory flow to estimate steady state three-dimensional wind fields for given free stream velocity forcing winds, atmospheric moisture advection, and cloud and precipitation microphysics proposed by Kessler (1969). The advantage of this modeling set-up is the computational efficiency as compared to regional mesoscale models such as the MM5. For this application, the Southern California region, comprised of the counties of Santa Barbara, Ventura, Los Angeles, Orange, and San Diego, and portions of San Bernardino and Riverside counties, are modeled at a 3-km resolution. The orographic precipitation model is forced by free stream wind velocities given by the 700mb winds from the NCEP Reanalysis I dataset. Atmospheric moisture initial conditions are defined also by the NCEP Reanalysis I dataset, and updated 4x- daily with the available 6-hourly NCEP Reanalysis forcing. This paper presents a comparison of the simulatedprecipitation to observations for over a variety of spatial scales and over the historical wet season periods from October 2000 to April 2005. The comparison is made over several performance measurements including (a) the occurrence/non-occurrence of precipitation, (b) overall bias and correlation, (c

Thermodynamic modeling is known as a promising tool for phase behavior modeling of asphaltene precipitation under different conditions such as pressure depletion and CO2 injection. In this work, a thermodynamic approach is used for modeling the phase behavior of asphaltene precipitation. The precipitated asphaltene phase is represented by an improved solid model, while the oil and gas phases are modeled with an equation of state. The PR-EOS was used to perform flash calculations. Then, the onset point and the amount of precipitated asphaltene were predicted. A computer code based on an improved solid model has been developed and used for predicting asphaltene precipitation data for one of Iranian heavy crudes, under pressure depletion and CO2 injection conditions. A significant improvement has been observed in predicting the asphaltene precipitation data under gas injection conditions. Especially for the maximum value of asphaltene precipitation and for the trend of the curve after the peak point, good agreement was observed. For gas injection conditions, comparison of the thermodynamic micellization model and the improved solid model showed that the thermodynamic micellization model cannot predict the maximum of precipitation as well as the improved solid model. The non-isothermal improved solid model has been used for predicting asphaltene precipitation data under pressure depletion conditions. The pressure depletion tests were done at different levels of temperature and pressure, and the parameters of a non-isothermal model were tuned using three onset pressures at three different temperatures for the considered crude. The results showed that the model is highly sensitive to the amount of solid molar volume along with the interaction coefficient parameter between the asphaltene component and light hydrocarbon components. Using a non-isothermal improved solid model, the asphaltene phase envelope was developed. It has been revealed that at high temperatures, an

Global Climate Models (GCMs) precipitation scenarios are often characterized by biases and coarse resolution that limit their direct application for basin level hydrological modeling. Bias-correction and spatial disaggregation methods are employed to improve the quality of ECHAM4/OPYC SRES A2 and B2 precipitation for the Ping River Basin in Thailand. Bias-correction method, based on gamma-gamma transformation, is applied to improve the frequency and amount of raw GCM precipitation at the grid nodes. Spatial disaggregation model parameters (β,σ2), based on multiplicative random cascade theory, are estimated using Mandelbrot-Kahane-Peyriere (MKP) function at q=1 for each month. Bias-correction method exhibits ability of reducing biases from the frequency and amount when compared with the computed frequency and amount at grid nodes based on spatially interpolated observed rainfall data. Spatial disaggregation model satisfactorily reproduces the observed trend and variation of average rainfall amount except during heavy rainfall events with certain degree of spatial and temporal variations. Finally, the hydrologic model, HEC-HMS, is applied to simulate the observed runoff for upper Ping River Basin based on the modified GCM precipitation scenarios and the raw GCM precipitation. Precipitation scenario developed with bias-correction and disaggregation provides an improved reproduction of basin level runoff observations.

Global Climate Models (GCMs) precipitation scenarios are often characterized by biases and coarse resolution that limit their direct application for basin level hydrological modeling. Bias-correction and spatial disaggregation methods are employed to improve the quality of ECHAM4/OPYC SRES A2 and B2 precipitation for the Ping River Basin in Thailand. Bias-correction method, based on gamma-gamma transformation, is applied to improve the frequency and amount of raw GCM precipitation at the grid nodes. Spatial disaggregation model parameters (β,σ2), based on multiplicative random cascade theory, are estimated using Mandelbrot-Kahane-Peyriere (MKP) function at q=1 for each month. Bias-correction method exhibits ability of reducing biases from the frequency and amount when compared with the computed frequency and amount at grid nodes based on spatially interpolated observed rainfall data. Spatial disaggregation model satisfactorily reproduces the observed trend and variation of average rainfall amount except during heavy rainfall events with certain degree of spatial and temporal variations. Finally, the hydrologic model, HEC-HMS, is applied to simulate the observed runoff for upper Ping River Basin based on the modified GCM precipitation scenarios and the raw GCM precipitation. Precipitation scenario developed with bias-correction and disaggregation provides an improved reproduction of basin level runoff observations.

The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

A long time series (1863--1984) of areal average precipitation in the vicinity of the Great Salt Lake is shown to be highly correlated with the Great Salt Lake levels. This time series is used to assess the unusual recent episode of heavyprecipitation (1981--1984). The Palmer Drought Severity Index (PDSI) is used to identify wet spells of weather. The cumulative excess precipitation during each wet spell was analyzed using stochastic frequency analysis. The analysis indicates that there were two very important wet spells in the time series, the beginning and ending in the 1860s and the most recent well spell which began in late 1981. The analysis suggests that the recent heavyprecipitation is not unexpected. Furthermore, if the climate of the past 122 years is representative of the climate over the next 100 years, another wet spell can be anticipated to be at least as severe, in terms of excess precipitation, as the 1981--1984 wet spell. Whether lake levels can recede to sufficiently low levels to prevent new record high levels during the next severe wet period is uncertain, but it must be considered in any long-term risk assessment strategies. 12 refs., 6 figs., 4 tabs.

A long time series (1863-1984) of areal-average precipitation in the vicinity of the Great Salt Lake is shown to be highly correlated with the Great Salt Lake levels. This time series is used to assess the unusualness of the recent episode of heavyprecipitation (1981 through 1984). The Palmer Drought Severity Index (PDSI) is used to identify wet spells of weather. The analysis indicates that there were two very important wet spells in the time series, one beginning and ending in the 1860s and the most recent wet spell which began in late 1981. The cumulative excess precipitation during each wet spell was analyzed using stochastic frequency analysis. The analysis suggests that the recent heavyprecipitation is not unexpected. Furthermore, if the climate of the past 100 years is representative of the climate over the next 100 years, another wet spell can be anticipated to be at least as severe, in terms of excess precipitation, as the 1981-1984 wet spell. Whether lake levels can recede to sufficiently low levels to prevent new record high levels during the next severe wet period is uncertain, but it must be considered in risk-assessment strategies.

In this work the authors investigate possible changes in the distribution of heavyprecipitation events under a warmer climate, using the results of a set of 20 climate models taking part in the Coupled Model Intercomparison Project phase 5 effort (CMIP5). Future changes are evaluated as the difference between the last four decades of the 21st and the 20th Century assuming the Representative Concentration Pathway RCP8.5 scenario. As a measure of the width of the right tail of the precipitation distribution, we use the difference between the 99th and the 90th percentiles. Despite a slight tendency to underestimate the observed heavyprecipitation, the considered CMIP5 models well represent the observed patterns in terms of the ensemble average, during both summer and winter seasons for the 1997-2005 period. Future changes in average precipitation are consistent with previous findings based on CMIP3 models. CMIP5 models show a projected increase for the end of the twenty-first century of the width of the right tail of the precipitation distribution, particularly pronounced over India, South East Asia, Indonesia and Central Africa during boreal summer, as well as over South America and southern Africa during boreal winter.

In this research, we study Albuquerque`s water and how it may be affected by changes in the regional climate, as manifested by variations in Rio Grande water levels. To do this, we rely on the use of coupled atmospheric, runoff, and ground water models. Preliminary work on the project has focused on uncoupled simulations of the aquifer beneath Albuquerque and winter precipitationsimulations of the upper Rio Grande Basin. The latter is discussed in this paper.

As part of the River Protection Project at Hanford, Washington, Bechtel National, Inc. has been contracted by the United States Department of Energy to design a Waste Treatment and Immobilization Plant to stabilize liquid radioactive waste. Because of its experience with radioactive waste stabilization, the Savannah River Technology Center of the Westinghouse Savannah River Company is working with Bechtel National and Washington Group International, to help design and test certain parts of the Waste Treatment Plant. One part of the process is the separation of radioactive isotopes from the liquid waste by a precipitation reaction and cross-flow ultrafiltration. To better understand those combined processes an experiment was performed using a simulated radioactive waste, made to prototypically represent the chemical and physical characteristics of a Hanford waste in tank 241-AN-102 and precipitated under prototypic conditions. The resultant slurry was then filtered using a cross-flow filter prototypic in porosity, length, and diameter to the plant design. An important aspect of filtration for waste treatment is the rate at which permeate is produced. There are many factors that affect filtration rate and one of the most difficult to obtain is the effect of particles in the waste streams. The Waste Treatment Plant will filter many waste streams, with varying concentrations and types of dissolved and undissolved solids. An added complication is the need to precipitate organic complexants so they can be efficiently separated from the supernatant. Depending on how precipitation is performed, the newly created solids will add to the complicating factors that determine permeate flux rate. To investigate the effect of precipitated solids on filter flux a pilot-scale test was performed and two different mixing mechanisms were used for the precipitation reaction. A standard impeller type mixer, which created a homogeneous mixture, and a pulse jet mixer, which created a

The summer Mei-yu event over eastern China, which is strongly influenced by large-scale circulation, is an important aspect of East Asian climate; for example, the Mei-yu frequently brings heavyprecipitation to the Yangtze-Huai River valley (YHRV). Both observations and a regional model were used to study the Mei-yu front and its relation to large-scale circulation during the summer of 1991 when severe floods occurred over YHRV. This study has two parts: the first part, presented here, analyzes the association between heavy Mei-yu precipitation and relevant large-scale circulation, while the second part, documented by W. Gong and W.-C. Wang, examines the model biases associated with the treatment of lateral boundary conditions (the objective analyses and coupling schemes) used as the driving fields for the regional model.Observations indicate that the Mei-yu season in 1991 spans 18 May-14 July, making it the longest Mei-yu period during the last 40 yr. The heavyprecipitation over YHRV is found to be intimately related to the western Pacific subtropical high, upper-tropospheric westerly jet at midlatitudes, and lower-tropospheric southwest wind and moisture flux. The regional model simulates reasonably well the regional mean surface air temperature and precipitation, in particular the precipitation evolution and its association with the large-scale circulation throughout the Mei-yu season. However, the model simulates smaller precipitation intensity, which is due partly to the colder and drier model atmosphere resulting from excessive low-level clouds and the simplified land surface process scheme used in the present study.

The accurate representation of precipitation is a recurring issue in global climate models, especially in the tropics. Poor skill in modeling the variability and climate teleconnections associated with El Niño/Southern Oscillation (ENSO) also persisted in the latest Climate Model Intercomparison Project (CMIP) campaigns. Observed ENSO precipitation teleconnections provide a standard by which we can judge a given model's ability to reproduce precipitation and dynamic feedback processes originating in the tropical Pacific. Using CMIP3 Atmospheric Model Intercomparison Project (AMIP) runs as a baseline, we compare precipitation teleconnections between models and observations, and we evaluate these results against available CMIP5 historical and AMIP runs. Using AMIP simulations restricts evaluation to the atmospheric response, as sea surface temperatures (SSTs) in AMIP are prescribed by observations. We use a rank correlation between ENSO SST indices and precipitation to define teleconnections, since this method is robust to outliers and appropriate for non-Gaussian data. Spatial correlations of the modeled and observed teleconnections are then evaluated. We look at these correlations in regions of strong precipitation teleconnections, including equatorial S. America, the "horseshoe" region in the western tropical Pacific, and southern N. America. For each region and season, we create a "normalized projection" of a given model's teleconnection pattern onto that of the observations, a metric that assesses the quality of regional pattern simulations while rewarding signals of correct sign over the region. Comparing this to an area-averaged (i.e., more generous) metric suggests models do better when restrictions on exact spatial dependence are loosened and conservation constraints apply. Model fidelity in regional measures remains far from perfect, suggesting intrinsic issues with the models' regional sensitivities in moist processes.

Remote sensing observations of precipitation typically utilize a number of instruments on various platforms. Ground validation campaigns incorporate ground-based and airborne measurements to characterize and study precipitating clouds, while the precipitation measurement constellation envisioned by the Global Precipitation Measurement (GPM) mission includes measurements from differing space-borne instruments. In addition to disparities such as frequency channel selection and bandwidth, measurement geometry and resolution differences between observing platforms result in inherent inconsistencies between data products. In order to harmonize measurements from multiple passive radiometers, a framework is required that addresses these differences. To accomplish this, we have implemented a flexible three-dimensional radiative transfer model. As its core, the radiative transfer model uses the Atmospheric Radiative Transfer Simulator (ARTS) version 2 to solve the radiative transfer equation in three dimensions using Monte Carlo integration. Gaseous absorption is computed with MonoRTM and formatted into look-up tables for rapid processing. Likewise, scattering properties are pre-computed using a number of publicly available codes, such as T-Matrix and DDSCAT. If necessary, a melting layer model can be applied to the input profiles. Gaussian antenna beams estimate the spatial resolutions of the passive measurements, and realistic bandpass characteristics can be included to properly account for the spectral response of the simulated instrument. This work presents three-dimensional simulations of WindSat brightness temperatures for an oceanic rain event sampled by the Tropical Rainfall Measuring Mission (TRMM) satellite. The 2B-31 combined Precipitation Radar / TRMM Microwave Imager (TMI) retrievals provide profiles that are the input to the radiative transfer model. TMI brightness temperatures are also simulated. Comparisons between monochromatic, pencil beam simulations and

The knowledge of the spatio-temporal distribution of precipitation is crucial to improve the understanding of the regional water cycle. So far precipitation fields derived from atmospheric models still suffer from large errors when it comes to reproducing the correct spatio-temporal distribution of rainfall fields. Usually stochastic precipitation fields conditioned on observations are more reliable. In our approach we derive precipitation fields with the copula-based method of random mixing. In a first step we generate different observation types, here rain gauge and microwave link measurements, from a virtual reality of the Neckar catchment (VR). These virtual observations mimic the advantages and disadvantages of the real observations. Rain gauges provide a high-quality information for a specific measurement point but their spatial representativeness is often rare. Microwave links, e. g. from commercial cellular operators, on the other hand can be used to estimate line integrals of near-surface rainfall information but they provide a very dense observational system. The precipitation fields of this stochastic interpolation, respectively simulation, are constrained on both, the point and line information. By using the virtual observations instead of real ones, we are able to compare the interpolated fields with the original fields. This allows us to evaluate the statistical precipitation fields in a very detailed manner in respect to the spatial and temporal resolution. In a further step we will use this method to simulateprecipitation fields constrained on real observations, which could be used for example as input data for surface-subsurface models or hydrological models.

This study investigates aerosol indirect effects on the development of heavy rainfall near Seoul, South Korea, on 12 July 2006, focusing on precipitation amount. The impact of the aerosol concentration on simulatedprecipitation is evaluated by varying the initial cloud condensation nuclei (CCN) number concentration in the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme. The simulations are performed under clean, semi-polluted, and polluted conditions. Detailed analysis of the physical processes that are responsible for surface precipitation, including moisture and cloud microphysical budgets shows enhanced ice-phase processes to be the primary driver of increased surface precipitation under the semi-polluted condition. Under the polluted condition, suppressed autoconversion and the enhanced evaporation of rain cause surface precipitation to decrease. To investigate the role of environmental conditions on precipitation response under different aerosol number concentrations, a set of sensitivity experiments are conducted with a 5 % decrease in relative humidity at the initial time, relative to the base simulations. Results show ice-phase processes having small sensitivity to CCN number concentration, compared with the base simulations. Surface precipitation responds differently to CCN number concentration under the lower humidity initial condition, being greatest under the clean condition, followed by the semi-polluted and polluted conditions.

The research reported here is part of a larger project that is coupling a suite of environmental models to simulate the hydrologic cycle within river basins (Bossert et al., 1999). These models include the Regional Atmospheric Modeling System (RAMS), which provides meteorological variables and precipitation to the Simulator for Processes of Landscapes, Surface/Subsurface Hydrology (SPLASH). SPLASH partitions precipitation into evaporation, transpiration, soil water storage, surface runoff, and subsurface recharge. The runoff is collected within a simple river channel model and the Finite element Heat and Mass (FEHM) subsurface model is linked to the land surface and river flow model components to simulate saturated and unsaturated flow and changes in aquifer levels. The goal is to produce a fully interactive system of atmospheric, surface hydrology, river and groundwater models to allow water and energy feedbacks throughout the system. This paper focuses on the evaluation of the precipitation fields predicted by the RAMS model at different times during the 1992--1993 water year in the Rio Grande basin. The evaluation includes comparing the model predictions to the observed precipitation as reported by Cooperative Summary of the Day and SNOTEL reporting stations.

Climate variability in the pre-instrumental period can be estimated either from climate proxy data or from numerical simulations. Both approaches still have considerable uncertainties and consistency tests are crucial for identifying robust features. One of the problems when comparing simulations with proxy-based reconstructions are potential scale mismatches. If the proxy-based reconstructions represent regional climate a direct comparison with simulated variables from global climate models, which in palaeoclimate applications are run with coarse resolutions, can lead to misleading results for two reasons: (i) the climate model might be biased even on large spatial scales, and (ii) small-scale spatial variability cannot be represented by the climate model. This problem can be expected to be particularly relevant for precipitation because of its high spatial variability. One way of addressing this problem is by applying downscaling techniques to the simulations. We have applied a statistical downscaling and correction method to precipitation from a simulation for the last millennium with the MPI for Meteorology Earth System Model, which uses ECHAM5-T31 as the atmosphere component. Our downscaling method, which is based on model output statistics (MOS), has been shown to outperform more standard (so-called perfect-prog) statistical downscaling methods when applied to simulatedprecipitation from the second half of the twentieth century, but it has not yet been applied to palaeoclimate simulations. Our aim is two-fold: to assess (a) whether downscaling using MOS yields additional information about long-term changes in regional climate and (b) to what extent the downscaled simulations may be in greater agreement with proxy-based reconstructions than raw model output. Two MOS downscaling methods, based on local scaling and principal component regression, are calibrated 'event-wise' (i.e. between contemporaneous sequences of simulated and observed events) using

Climate change includes not only changes in mean climate but also in weather extremes. For a few prominent heatwaves and heavyprecipitation events a human contribution to their occurrence has been demonstrated. Here we apply a similar framework but estimate what fraction of all globally occurring heavyprecipitation and hot extremes is attributable to warming. We show that at the present-day warming of 0.85 °C about 18% of the moderate daily precipitation extremes over land are attributable to the observed temperature increase since pre-industrial times, which in turn primarily results from human influence. For 2 °C of warming the fraction of precipitation extremes attributable to human influence rises to about 40%. Likewise, today about 75% of the moderate daily hot extremes over land are attributable to warming. It is the most rare and extreme events for which the largest fraction is anthropogenic, and that contribution increases nonlinearly with further warming. The approach introduced here is robust owing to its global perspective, less sensitive to model biases than alternative methods and informative for mitigation policy, and thereby complementary to single-event attribution. Combined with information on vulnerability and exposure, it serves as a scientific basis for assessment of global risk from extreme weather, the discussion of mitigation targets, and liability considerations.

The Advanced Regional Eta-coordinate Model (AREM) is used to explore the predictability of a heavy rainfall event along the Meiyu front in China during 3-4 July 2003. Based on the sensitivity of precipitation prediction to initial data sources and initial uncertainties in different variables, the evolution of error growth and the associated mechanism are described and discussed in detail in this paper. The results indicate that the smaller-amplitude initial error presents a faster growth rate and its growth is characterized by a transition from localized growth to widespread expansion error. Such modality of the error growth is closely related to the evolvement of the precipitation episode, and consequently remarkable forecast divergence is found near the rainband, indicating that the rainfall area is a sensitive region for error growth. The initial error in the rainband contributes significantly to the forecast divergence, and its amplification and propagation are largely determined by the initial moisture distribution. The moisture condition also affects the error growth on smaller scales and the subsequent upscale error cascade. In addition, the error growth defined by an energy norm reveals that large error energy collocates well with the strong latent heating, implying that the occurrence of precipitation and error growth share the same energy source—the latent heat. This may impose an intrinsic predictability limit on the prediction of heavyprecipitation.

From the suite of future Global Precipitation Mission (GPM) satellites we have selected 11 of the possible contributors to the NASA's International precipitation measurement program. The Observing System Simulation Experiments (OSSE) presented here explores the predictive usefulness of this suite of satellites. In order to carry out such experiments a Nature Run based on results from a state of the model is required. For that purpose we have selected recent past runs from the European Center for Medium Range Forecasts (ECMWF). These were designated as special data sets for OSSEs in partnership between NASA, NCEP/EMC, and NOAA. In order to test the usefulness of these future GPM-based precipitation measurements we first identify the typical orbits of eleven satellites. Along these orbital tracks we generate proxy precipitation data sets from the ECMWF Nature Run. This method of extraction of precipitation data set from a Nature Run is described in this paper. This methodology also requires a fraternal twin model (different from the Nature Run) in which the usefulness of the proposed GPM proxy data sets from the Nature Run are systematically evaluated in a forecast mode. The procedure for incorporation of the rainfall data sets is called the rain rate initialization. Data from one or more satellites are sequentially introduced into the fraternal twin model (which is the Florida State University Global Spectral Model) during the initialization phase for a number of experiments. After the initialization of such precipitation data sets, forecast experiments are carried out with the fraternal twin. The question asked is, as we introduce more and more GPM satellites how close do the forecasts from the fraternal twin approach the Nature Run? The results from this experimentation show that very promising improvements for short-range precipitation forecast skills are attainable from the proposed suite of GPM satellites.

A numerical model based on smoothed particle hydrodynamics (SPH) was developed for reactive transport and mineral precipitation in fractured and porous materials. Because of its Lagrangian particle nature, SPH has several advantages for modeling Navier-Stokes flow and reactive transport including: (1) in a Lagrangian framework there is no non-linear term in the momentum conservation equation, so that accurate solutions can be obtained for momentum dominated flows and; (2) complicated physical and chemical processes such as surface growth due to precipitation/dissolution and chemical reactions are easy to implement. In addition, SPH simulations explicitly conserve mass and linear momentum. The SPH solution of the diffusion equation with fixed and moving reactive solid-fluid boundaries was compared with analytical solutions, Lattice Boltzmann [Q. Kang, D. Zhang, P. Lichtner, I. Tsimpanogiannis, Lattice Boltzmann model for crystal growth from supersaturated solution, Geophysical Research Letters, 31 (2004) L21604] simulations and diffusion limited aggregation (DLA) [P. Meakin, Fractals, scaling and far from equilibrium. Cambridge University Press, Cambridge, UK, 1998] model simulations. To illustrate the capabilities of the model, coupled three-dimensional flow, reactive transport and precipitation in a fracture aperture with a complex geometry were simulated.

This study evaluates the model-simulated stream discharge over the Guadalupe River basin in central Texas driven by three precipitation products: the Guadalupe-Blanco River Authority (GBRA) rain gauge network, the Next Generation Weather Radar (NEXRAD) Stage ΙΙΙ precipitation product, and the Tropical Rainfall Measurement Mission (TRMM) 3B42 product. Focus will be on results from the Upper Guadalupe River sub-basin. This sub-basin is more prone to flooding due to its geological properties (thin soils, exposed bedrock, and sparse vegetation) and the impact of Balcones Escarpment on the moisture coming from the Gulf of Mexico. The physically based, distributed-parameter Gridded Surface Subsurface Hydrologic Analysis (GSSHA) hydrologic model was used to simulate the June-2002 flooding event. Simulations driven by NEXRAD Stage ΙΙΙ 15 - min precipitation yielded better results with low RMSE (88.3%), high NSE (0.6), high R2 (0.73), low RSR (0.63) and low PBIAS (-17.3%) compared to simulations driven by the other products.

Recent advances in Global Positioning System (GPS) remote sensing technology allow for a direct estimation of the precipitable water vapor (PWV) from delayed signals transmitted by GPS satellites, which can be assimilated into numerical models with four-dimensional variational (4DVAR) data assimilation. A mesoscale model and its 4DVAR system are used to access the impacts of assimilating GPS-PWV and hourly rainfall observations on the short-range prediction of a heavy rainfall event on 20 June 2002. The heavyprecipitation was induced by a sequence of meso- β-scale convective systems (MCS) along the mei-yu front in China. The experiments with GPS-PWV assimilation successfully simulated the evolution of the observed MCS cluster and also eliminated the erroneous rainfall systems found in the experiment without 4DVAR assimilation. Experiments with hourly rainfall assimilation performed similarly both on the prediction of MCS initiation and the elimination of erroneous systems, however the MCS dissipated much sooner than it did in observations. It is found that the assimilation-induced moisture perturbation and mesoscale low-level jet are helpful for the MCS generation and development. It is also discovered that spurious gravity waves may post serious limitations for the current 4DVAR algorithm, which would degrade the assimilation efficiency, especially for rainfall data. Sensitivity experiments with different observations, assimilation windows and observation weightings suggest that assimilating GPS-PWV can be quite effective, even with the assimilation window as short as 1 h. On the other hand, assimilating rainfall observations requires extreme cautions on the selection of observation weightings and the control of spurious gravity waves.

Hungarian Meteorological Service1 Budapest University of Technology and Economics2 Precipitation is one of the the most important meteorological parameters describing the state of the climate and to get correct information from trends, accurate measurements of precipitation is very important. The problem is that the precipitation measurements are affected by systematic errors leading to an underestimation of actual precipitation which errors vary by type of precipitaion and gauge type. It is well known that the wind speed is the most important enviromental factor that contributes to the underestimation of actual precipitation, especially for solid precipitation. To study and correct the errors of precipitation measurements there are two basic possibilities: · Use of results and conclusion of International Precipitation Measurements Intercomparisons; · To build standard reference gauges (DFIR, pit gauge) and make own investigation; In 1999 at the HMS we tried to achieve own investigation and built standard reference gauges But the cost-benefit ratio in case of snow (use of DFIR) was very bad (we had several winters without significant amount of snow, while the state of DFIR was continously falling) Due to the problem mentioned above there was need for new approximation that was the modelling made by Budapest University of Technology and Economics, Department of Fluid Mechanics using the FLUENT 6.2 model. The ANSYS Fluent package is featured fluid dynamics solution for modelling flow and other related physical phenomena. It provides the tools needed to describe atmospheric processes, design and optimize new equipment. The CFD package includes solvers that accurately simulate behaviour of the broad range of flows that from single-phase to multi-phase. The questions we wanted to get answer to are as follows: · How do the different types of gauges deform the airflow around themselves? · Try to give quantitative estimation of wind induced error. · How does the use

In the absence of an intrinsic dipole magnetic field, Mars' O+ planetary ions are accelerated by the solar wind. Because of their large gyroradius, a population of these planetary ions can precipitate back into Mars' upper atmosphere with enough energy to eject neutrals into space via collision. This process, referred to as sputtering, may have been a dominant atmospheric loss process during earlier stages of our Sun. Yet until now, a limited number of observations have been possible; Analyzer of Space Plasmas and Energetic Atoms-3/Mars Express observed such a precipitation only during extreme conditions, suggesting that sputtering might be not as intense as theoretically predicted. Here we describe one example of precipitation of heavy ions during quiet solar conditions. Between November 2014 and April 2015, the average precipitating flux is significant and in agreement with predictions. From these measured precipitating fluxes, we estimate that a maximum of 1.0 × 1024 O/s could have been lost due to sputtering.

Water resources assessments for future climates require meaningful simulations of likely precipitation and evaporation for simulation of flow and derived quantities of interest. The current approach for making such assessments involve using simulations from one or a handful of General Circulation Models (GCMs), for usually one assumed future greenhouse gas emission scenario, deriving associated flows and the planning or design attributes required, and using these as the basis of any planning or design that is needed. An assumption that is implicit in this approach is that the single or multiple simulations being considered are representative of what is likely to occur in the future. Is this a reasonable assumption to make and use in designing future water resources infrastructure? Is the uncertainty in the simulations captured through this process a real reflection of the likely uncertainty, even though a handful of GCMs are considered? Can one, instead, develop a measure of this uncertainty for a given GCM simulation for all variables in space and time, and use this information as the basis of water resources planning (similar to using "input uncertainty" in rainfall-runoff modelling)? These are some of the questions we address in course of this presentation. We present here a new basis for assigning a measure of uncertainty to GCM simulations of precipitation and temperature. Unlike other alternatives which assess overall GCM uncertainty, our approach leads to a unique measure of uncertainty in the variable of interest for each simulated value in space and time. We refer to this as an error model of GCM precipitation and temperature simulations, to allow a complete assessment of the merits or demerits associated with future infrastructure options being considered, or mitigation plans being devised. The presented error model quantifies the error variance of GCM monthly precipitation and temperature, and reports it as the Square Root Error Variance (SREV

The soil water index (SWI) from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient (CORR), root-mean-squaxe-error (RMSE) and bias (BIAS) shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture (NCEP) in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13-14 June, 18-22 June, and 21-26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulatedprecipitation from SWI are better than those from NCEP and closer to the observed values. The simulatedheavy rainfall for 21-26 July shows that the update of soil moisture initial conditions can improve the model's performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13-14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy rainfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI.

Land use and land cover maps and their physical-chemical and biological properties are important variables in the numerical modeling of Earth systems. In this context, the main objective of this study is to analyze the improvements resulting from the land use and land cover map update in numerical simulations performed using the Regional Climate Model system version 4 (RegCM4), as well as the seasonal variations of physical parameters used by the Biosphere Atmosphere Transfer Scheme (BATS). In general, the update of the South America 2007 land use and land cover map, used by the BATS, improved the simulation of precipitation by 10 %, increasing the mean temporal correlation coefficient, compared to observed data, from 0.84 to 0.92 (significant at p < 0.05, Student's t test). Correspondingly, the simulations performed with adjustments in maximum fractional vegetation cover, in visible and shortwave infrared reflectance, and in the leaf area index, showed a good agreement for maximum and minimum temperature, with values closer to observed data. The changes in physical parameters and land use updating in BATS/RegCM4 reduced overestimation of simulatedprecipitation from 19 to 7 % (significant at p < 0.05, Student's t test). Regarding evapotranspiration and precipitation, the most significant differences due to land use updating were located (1) in the Amazon deforestation arc; (2) around the Brazil-Bolivia border (in the Brazilian Pantanal wetlands); (3) in the Northeast region of Brazil; (4) in northwestern Paraguay; and (5) in the River Plate Basin, in Argentina. Moreover, the main precipitation differences between sensitivity and control experiments occurred during the rainy months in central-north South America (October to March). These were associated with a displacement in the South Atlantic convergence zone (SACZ) positioning, presenting a spatial pattern of alternated areas with higher and lower precipitation rates. These important differences occur due to the

Stochastic models, based on diverse stochastic processes, have been applied in the last decades for the simulation of precipitation time series. Different models target a good reproduction of statistical properties of precipitation across a specific range of temporal scales. The choice of the statistical properties and the respective range of scales are frequently dictated by the purpose for which each model is built. Despite the large variety of stochastic precipitation modeling tools, an intercomparison has been rarely attempted. Moreover, a common practice is to validate a stochastic model only for the statistical properties for which it has been developed to perform well. It is our opinion that this practice may have negative implications, especially when stochastic models are used in hydrology as a black box. In this study we present an extensive comparison among some of the most widely applied stochastic precipitation models. Models based on point processes (e.g. Neyman-Scott rectangular pulses model, Bartlett-Lewis rectangular pulses model), Mutiplicative Random Cascades (e.g. canonical and microcanonical MRC), Markov chains, scaling processes and their combinations (e.g. Paschalis et al., 2013, Advances in Water resources) are used in order to assess their efficiency for a number of stations belonging to different climates, spanning from semiarid to wet oceanic. A complete model validation is performed, taking into account all the essential statistical properties of precipitation (e.g. probability distribution, extremes, autocorrelation, intermittency, etc.) for a wide range of temporal scales relevant for hydrological and ecological applications. The overall goal is to identify the general patterns of the strengths and weaknesses of the various modeling tools, and to provide insights for generally applicable guidelines in the model selection dependent on the specific hydrological/ecological application.

Second quarter progress report for year 3 on contract NASW-99002 "What is the Relationship between heavy ion outflow and high latitude energetic particle precipitation". In this Project we are studying the relationship between the fluxes, mean energies, and field-aligned flow speeds of escaping suprathermal H+ and 0+ measured by the TEAMS instrument on FAST and the energy flux of precipitating electrons obtained from the LBHL images taken by the UVI camera on POLAR. In this portion of the project we are using UVI images to tell us when substorm onsets occur and how the auroral zone changes during the course of a substorm. We are correlating this information with TEAMS flux measurements made over the auroral zone at times close to these substorms. The goal is to understand how the flux of suprathermal ion outflow varies with substorm phase.

Heavyprecipitation events and subsequent flash floods are one of the most dramatic hazards in many regions such as the Mediterranean basin as recently stressed in the HyMeX (HYdrological cycle in the Mediterranean EXperiment) international programme. The focus of this study is to assess the quality of very short range (below 3 hour lead times) precipitation forecasts based on weather radar nowcasting system. Specific nowcasting amounts of 10 and 30 minutes generated with a nowcasting technique (Berenguer et al 2005, 2011) are compared against raingauge observations and also weather radar precipitation estimates observed over Catalonia (NE Spain) using data from the Meteorological Service of Catalonia and the Water Catalan Agency. Results allow to discuss the feasibility of issuing warnings for different precipitation amounts and lead times for a number of case studies, including very intense convective events with 30minute precipitation amounts exceeding 40 mm (Bech et al 2005, 2011). As indicated by a number of verification scores single based radar precipitation nowcasts decrease their skill quickly with increasing lead times and rainfall thresholds. This work has been done in the framework of the Hymex research programme and has been partly funded by the ProFEWS project (CGL2010-15892). References Bech J, N Pineda, T Rigo, M Aran, J Amaro, M Gayà, J Arús, J Montanyà, O van der Velde, 2011: A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis. Atmospheric Research 100:621-637 http://dx.doi.org/10.1016/j.atmosres.2010.12.024 Bech J, R Pascual, T Rigo, N Pineda, JM López, J Arús, and M Gayà, 2007: An observational study of the 7 September 2005 Barcelona tornado outbreak. Natural Hazards and Earth System Science 7:129-139 http://dx.doi.org/10.5194/nhess-7-129-2007 Berenguer M, C Corral, R Sa0nchez-Diezma, D Sempere-Torres, 2005: Hydrological validation of a radar based nowcasting technique. Journal of

Numerical simulations show that a simple model for the formation of Liesegang precipitation patterns, which takes into account the dependence of nucleation and particle growth kinetics on supersaturation, can explain not only simple patterns like parallel bands in a test tube or concentric rings in a petri dish, but also more complex structural features, such as dislocations, helices, "Saturn rings," or patterns formed in the case of equal initial concentrations of the source substances. The limits of application of the model are discussed. (c) 1994 American Institute of Physics. PMID:12780140

This study investigates the refined simulation skill that results when the regional Climate extension of the Weather Research and Forecasting (CWRF) model is nested in the ECMWF Hamburg version 4.5 (ECHAM) atmospheric general circulation model over the United States during 1980-2009, where observed sea surface temperatures are used in both models. Over the contiguous US, for each of the four seasons from winter to fall, CWRF reduces the root mean square error of the ECHAM seasonal mean surface air temperature simulation by 0.19, 0.82, 2.02 and 1.85 °C, and increases the equitable threat score of seasonal mean precipitation by 0.18, 0.11, 0.09 and 0.12. CWRF also simulates much more realistically daily precipitation frequency and heavyprecipitation events, typically over the Central Great Plains, Cascade Mountains and Gulf Coast States. These CWRF skill enhancements are attributed to the increased spatial resolution and physics refinements in representing orographic, terrestrial hydrology, convection, and cloud-aerosol-radiation effects and their interactions. Empirical orthogonal function analysis of seasonal mean precipitation and surface air temperature interannual variability shows that, in general, CWRF substantially improves the spatial distribution of both quantities, while temporal evolution (i.e. interannual variability) of the first 3 primary patterns is highly correlated with that of the driving ECHAM (except for summer precipitation), and they both have low temporal correlations against observations. During winter, when large-scale forcing dominates, both models also have similar responses to strong ENSO signals where they successfully capture observed precipitation composite anomalies but substantially fail to reproduce surface air temperature anomalies. When driven by the ECMWF Reanalysis Interim, CWRF produces a very realistic interannual evolution of large-scale precipitation and surface air temperature patterns where the temporal correlations with

The space-time statistics of short-term precipitation is studied for two cities in northern Europe, and related to radiosonde observations. The motivation is to construct the temporally varying parameters needed to drive a stochastic short-term precipitation generator. Moments, intermittency, semivariograms, temporal covariance and advection parameters need to be characterised in order to produce realistic scenario simulations for extreme value estimation at different scales. It is hoped that the temporal variability in these parameters can be related to radiosonde data. Hourly values from 46 precipitation stations within a 100*130 km2 region around Copenhagen during the period 1979-2012 is analysed. Bi-daily radiosonde profiles are present from 1969 to 2006. These soundings (vertical profiles of temperature, dew point and wind vector) describe the atmospheric moisture content and convective potential of the current weather situation. Preliminary analysis show that some of the indices extracted from the 12h radiosonde data show good temporal autocorrelation, supporting interpolation to match the 1-hour precipitation data. The precipitation data show a rapidly decreasing temporal autocorrelation function (typically below 0.5 above approx. 12 km), indicating that there is a high variance fraction below scales that the station network is able to reveal. The second data set consists of 7.5-minute C-band radar data from Trondheim, available from June 2013 to October 2015. During the 2014 and 2015 summer seasons, around 25 tipping-bucket precipitation gauges within a 15*20 km area supply observations with temporal resolution down to minute-scale. Nearby radiosonde data are available bi-daily from 1963 to 2015. These data will be explored to provide insight in high-frequency spatial and temporal variability not detectable from the long-term Copenhagen data set. The analysis is a part of the EU-7FP project "Pearl" (http://www.pearl-fp7.eu/, Greve case study), the Norwegian

Floods are costly natural disasters, causing significant loss of life and destruction of property. Understanding how floods will change with climate in the coming decades is therefore of considerable interest. Existing studies largely focus on changes in precipitation extremes and assume that this extends to floods. However, it is unclear that an increase in more intense precipitation automatically translates into an increase in flooding. For example, large-scale floods are not the result of extreme 1-day rainfall. Rather it is the long-term precipitation dynamics combined with basin characteristics that dictate the relationship between heavy rainfall and flood events. This study tackles two open questions that need to be explored to understand the appropriate approach to projections of future flooding. First, we must understand how basin size influences the relationship between basin rainfall and the resulting floods. To tackle this question, we use historical precipitation and streamflow records for 165 basins in the Ohio River. Results indicate that 1-day rainfall and peak streamflow are highly correlated in small basins. For larger basins (>2000 square miles), 7-day rainfall has the strongest correlation with peak flood flows. This informs what variables must be considered when examining how changes in precipitation extremes may translate into flood events. Second, many studies analyzing the response of hydrologic systems to climate change involve downscaling climate information and feeding it through a hydrologic model. This raises questions of the appropriate resolution for accurate flood modeling. In order to understand the effect spatial and temporal resolution have on modeled flooding, we performed model experiments with the Variable Infiltration Capacity (VIC) model. These experimental results can inform future studies that seek to understand how flood regimes will change with climate.

A numerical simulation code is developed to evaluate the loss rate of particles trapped in a mirror magnetic field geometry with asymmetric loss cones. The one-dimensional model can accommodate particle diffusion at any prescribed rate and loss cones of any prescribed sizes, and it incorporates the important effect of atmospheric backscattering. Numerical solutions for the loss cone particle distribution function calculated for the case of equal loss cones provide an acceptable simulation of the well-known modified Bessel function solution. The code provides the first quantitative solutions for any specified rate of pitch angle scattering for the general case of arbitrary asymmetry in loss cone size. In the case of weak or moderate diffusion the ratio of particle precipitation fluxes into the two loss cones can provide a sensitive measurement of the rate of particle scattering, but to utilize this important diagnostic property, one must also have information on the fraction of particles that are backscattered from the atmosphere.

Energy spectra of electron microbursts from 170 keV to 340 keV have been measured by the solid-state detectors aboard the low-altitude (680 km) polar-orbiting Korean STSAT-1 (Science and Technology SATellite). These measurements have revealed two important characteristics unique to the microbursts: (1) They are produced by a fast-loss cone-filling process in which the interaction time for pitch-angle scattering is less than 50 ms and (2) The e-folding energy of the perpendicular component is larger than that of the parallel component, and the loss cone is not completely filled by electrons. To understand how wave-particle interactions could generate microbursts, we performed a test particle simulation and investigated how the waves scattered electron pitch angles within the timescale required for microburst precipitation. The application of rising-frequency whistler-mode waves to electrons of different energies moving in a dipole magnetic field showed that chorus magnetic wave fields, rather than electric fields, were the main cause of microburst events, which implied that microbursts could be produced by a quasi-adiabatic process. In addition, the simulation results showed that high-energy electrons could resonate with chorus waves at high magnetic latitudes where the loss cone was larger, which might explain the decreased e-folding energy of precipitated microbursts compared to that of trapped electrons.

In the densely populated region of East Asia, it is important to know the mechanism, scale, and frequency of heavyprecipitation brought about during the monsoons and typhoons. However, observational data, which cover only several decades, are insufficient to examine the long-term trend of extreme precipitation and its background mechanism. In humid areas, the transport flux of a suspended detrital material through a river system is known to have an empirical power relationship with precipitation. Thus, the sedimentation flux of a fine detrital material could potentially be used as a proxy for reconstructing past heavyprecipitation events. To test the idea that the sedimentation flux of detrital materials records past heavyprecipitation events (e.g., typhoons), we focused on the detrital flux estimated from the annually laminated sediment of Lake Suigetsu, central Japan, which is capable of accurately correlating the age of detrital flux with the precipitation record. We first established a precise age model (error within ±1 year in average) beginning in 1920 A.D. on the basis of varve counting fine-tuned by correlation between event layers with historical floods. The flux of the detrital material (g/cm2/year) was estimated on the basis of Al2O3 content (wt%), dry bulk density (g/cm3), and sedimentation rate (cm/year) calculated from the age model. The detrital flux of background sedimentation showed a weak positive correlation with annual and monthly (June and September) precipitation excluding heavyprecipitation that exceeded 100 mm/day. Furthermore, the thickness of instantaneous event layers, which corresponds to several maxima of detrital flux and is correlated with floods that occurred mainly during typhoons, showed a positive relationship with the total amount of precipitation that caused a flood event. This result suggests that the detrital flux maxima (deposition of event layers) record past extreme precipitation events that were likely associated with

The autumn atmospheric conditions associated with HeavyPrecipitation Events (HPEs) in the western mediterranean region and differences with respect to the seasonal-mean conditions are investigated. Seasonal high-resolution simulations from the regional climate model COSMO-CLM covering the autumn periods of 2011 and 2012 are used. Atmospheric conditions at five different subdomains surrounding the western Mediterranean are considered, namely France, Italy (North and South), Spain, and North Africa. During HPEs, moisture and instability sources are located generally upstream of the target area over the sea, being transported by fast low-level winds towards the HPE areas. Concentration of high humidity over land and initiation of convection are highly related to the orography in the area. Stronger convective precipitation events occur at mid-level elevations rather than at higher altitudes. The significant increase in atmospheric moisture and instability, identified prior to HPEs, builds up in two different time lengths: atmospheric moisture increase could be traced back to at least 6-24 h before the initiation stage of the event, whereas an increase of Convective Available Potential Energy (CAPE) is detected in the hours prior to the event during the mature stage. The most intense HPEs are in general associated with higher values of integrated water vapour, CAPE, and low-level and mid-tropospheric wind speed. During HPEs in all subdomains, the dominant precipitation peak occurs between 1200 and 1800 UTC suggesting that convective precipitation prevails in most HPEs. The diurnal cycle of integrated water vapour during the mature stage of HPEs shows that the atmosphere remains wetter than average for most of the period and that only a decrease is seen after the afternoon precipitation peak. Negligible CAPE characterizes mean-seasonal conditions while the classical diurnal cycle with the peak in the early afternoon and much higher mean values occur during HPE events

Heavy rainfall in central Europe is one of the assumed effects of climate change, which occurs with large seasonal and regional differences in its magnitude. The extent of loss depends on natural parameters (e.g. topography and vegetation) as well as on socio-economic factors like urbanized and industrialized areas and population density. Dangerous cascade effects appear, if critical infrastructure like the electrical power supply is affected. In some cases mudflows and flash floods cause inundated or undercut roads and cause a high demand for fast and effective assistance of the authorities. The civil protection in Germany is based on a federal system with a bottom-up command-structure and responsibility to the local community. Commonly this responsibility is taken by the fire brigades and civil protection units of the community or district. After heavy rainfall in an urban area, numerous incidents and emergency calls appearing at a time are overstressing the human and technical resources of the fire brigades within the local authority frequently. In this study, a method of comprehensive evaluation of meteorological data and the operation data from local fire brigades shall be developed for the Rhine-Main-Area in order to identify particular affected spots of heavy rain and bundle resources of the fire brigades. It is to be found out if the study area contains regions with a particularly high exposure to heavy rain and high application numbers of the fire department and whether there is a relationship of rainfall and frequency of use. To evaluate particular local effects on the fire brigades capability, a brief analysis of the meteorological data provided by the German Meteorological Service (DWD) as well as the evaluation of the incident data of the affected fire brigades, is used to frame a realistic approach. In particular fire brigade operation data can be used accordingly to describe the intensity of the aftermath when heavyprecipitation strikes a certain

A rainfall simulator, developed on the principle of droplet formation from needle tips, is described. The simulator is designed for laboratory experimentation to examine the effects of acidic precipitation on terrestrial plants. Droplet diameter can be varied from 2.5 to 3.4 mm with different gauge needles, and rainfall intensities from 0.50 to 1.25 cm h/sup -1/ can be attained by a variable speed peristaltic pump. Uniform distribution of rainfall was achieved by rotating the target area and by spacing needles, using an empirical cumulative probability distribution function, along eight radial tubular arms. Variation in rainfall distribution across a 1.2 m diameter circular target area was < 5%. Integrity of solution chemistry was maintained upon passage through the simulator with variations in cation concentrations < 10%, anion concentrations < 5% and pH < 0.2. The system offers sufficient flexibility to simulate a range of rainfall characteristics by varying needle diameter, changing pump speed and/or altering the number of radial arms on each unit.

The precipitation of biogenic Mn oxides at acidic pH is rarely reported and poorly understood, compared to biogenic Mn oxide precipitation at near neutral conditions. Here we identified and investigated the precipitation of biogenic Mn oxides in acidic soil, and studied their role in the retention of heavy metals, at the former uranium mining site of Ronneburg, Germany. The site is characterized by acidic pH, low carbon content and high heavy metal loads including rare earth elements. Specifically, the Mn oxides were present in layers identified by detailed soil profiling and within these layers pH varied from 4.7 to 5.1, Eh varied from 640 to 660 mV and there were enriched total metal contents for Ba, Ni, Co, Cd and Zn in addition to high Mn levels. Using electron microprobe analysis, synchrotron X-ray diffraction and X-ray absorption spectroscopy, we identified poorly crystalline birnessite (δ-MnO2) as the dominant Mn oxide in the Mn layers, present as coatings covering and cementing quartz grains. With geochemical modelling we found that the environmental conditions at the site were not favourable for chemical oxidation of Mn(II), and thus we performed 16S rDNA sequencing to isolate the bacterial strains present in the Mn layers. Bacterial phyla present in the Mn layers belonged to Firmicutes, Actinobacteria and Proteobacteria, and from these phyla we isolated six strains of Mn(II) oxidizing bacteria and confirmed their ability to oxidise Mn(II) in the laboratory. The biogenic Mn oxide layers act as a sink for metals and the bioavailability of these metals was much lower in the Mn layers than in adjacent layers, reflecting their preferential sorption to the biogenic Mn oxide. In this presentation we will report our findings, concluding that the formation of natural biogenic poorly crystalline birnessite can occur at acidic pH, resulting in the formation of a biogeochemical barrier which, in turn, can control the mobility and bioavailability of heavy metals in

We apply a recently proposed algorithm for disaggregating observed precipitation data into predominantly convective and stratiform, and evaluate biases in characteristics of parameterized convective (subgrid) and stratiform (large-scale) precipitation in an ensemble of 11 RCM simulations for recent climate in Central Europe. All RCMs have a resolution of 25 km and are driven by the ERA-40 reanalysis. We focus on mean annual cycle, proportion of convective precipitation, dependence on altitude, and extremes. The results show that characteristics of total precipitation are often better simulated than are those of convective and stratiform precipitation evaluated separately. While annual cycles of convective and stratiform precipitation are reproduced reasonably well in most RCMs, some of them consistently and substantially overestimate or underestimate the proportion of convective precipitation throughout the year. Intensity of convective precipitation is underestimated in all RCMs. Dependence on altitude is also simulated better for stratiform and total precipitation than for convective precipitation, for which several RCMs produce unrealistic slopes. Extremes are underestimated for convective precipitation while they tend to be slightly overestimated for stratiform precipitation, thus resulting in a relatively good reproduction of extremes in total precipitation amounts. The results suggest that the examined ensemble of RCMs suffers from substantial deficiencies in reproducing precipitation processes and support previous findings that climate models' errors in precipitation characteristics are mainly related to deficiencies in the representation of convection.

We extend the advantages of Lagrangian random walk particle tracking (RWPT) methods that have long been used to simulate advection and dispersion in highly heterogeneous media. By formulating dissolution as a random, independent decay process, the classical continuum rate law is recovered. Formulating the random precipitation process requires a consideration of the probability that two nearby particles will coincide in a given time period. This depends on local mixing (as by diffusion) and the total domain particle number density, which are fixed and therefore easy to calculate. The result is that the classical law of mass action for equilibrium reactions can be reproduced in an ensemble sense. The same number of parameters for A+B ⇌ C are needed in a probabilistic versus continuum reaction simulation-- —one each for forward and backward probabilities that correspond to rates. The random nature of the simulations allows for significant disequilibrium in any given region at any time that is independent of the numerical details such as time stepping or particle density. This is exemplified by nearby or intermingled groups of reactants and little or no product--—a result that is often noted in the field that is difficult to reconcile with continuum methods or coarse-grained Eulerian models. Our results support recent results of perturbed advection-dispersion-reaction continuum models (Luo et al., WRR 44, 2008), and suggest that many different kinds of reactions can be easily added to existing RWPT codes.

For the first time ever, GNSS Radio Occultastion measurements will be taken at two polarizations, to exploit the potential capabilities of polarimetric radio occultation for detecting and quantifying heavyprecipitation events and other de-polarizing atmospheric effects (e.g. cloud ice). We report the results on discriminating rain from a mountain top experiment set up to identify and understand the factors that affect the polarimetric RO signal by collecting heavy rain together with free-rain data.

This document is the fourth quarter progress report for year two on contract NAW-99002 'What is the relationship between heavy ion outflow and high latitude energetic particle precipitation'. In this project we are studying the relationship between the fluxes, mean energies, and field-aligned flow speeds of escaping suprathermal H+ and O+ measured by the TEAMS instrument on FAST and the energy flux of precipitating electrons obtained form the LBHL images taken by the Ultraviolet Imagery (UVI) camera on the Polar spacecraft. We have analyzed data from three time intervals, 7-11 Feb, 25-31 Jan, and 1-6 Feb 1997. We find that there indeed is a relationship between the O+ escape fluxes and the intensity of the aurora at the foot point of the field line. The time delay between an auroral intensification and the corresponding increase in escape flux is very short, only a few minutes. At low auroral luminosity the relationship between escape flux and luminosity appears to break down due possibly to the lack of sensitivity of the auroral emissions to large fluxes of low energy electrons.

Spatial and temporal variability of rainfall over Africa offers considerable challenges on climate change over the region. This is because of the complexity of regional climates in Africa and their associated geographic features. Adding to that complexity are deserts, vegetation variations, numerous mountain chains that can alter regional climate and weather patterns, the influence of the land-sea contrast due to the presence of several large lakes and the surrounding Indian and Atlantic Oceans. This leads to strong fluctuations of rainfall that may cause drought and flood in the region. Therefore, being able to simulate the spatial distribution of mean precipitation is quite important but also capturing their occurrences and intensities is critical for Africa whose economy relies on rain-fed agriculture. The International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM3), driven by the newly produced ERA-Interim reanalysis, is used to investigate this issue. Several indices, such as the number of wet days and their intensity, maximum dry and wet spells length and the frequency of heavyprecipitation days, are used to characterize the spatial variability of seasonal extreme rainfall over continental Africa. Model results are compared to both TRMM and FEWS rainfall data. They indicate that although the model captures the location of longest and shortest wet and dry spells, it tends to extend slightly the wet spell length around mountainous regions and along the ITCZ and the dry spell length over northern and southern Africa during austral and boreal summer respectively. This is mainly visible when compared to FEWS. Extension of the wet spell length may be partly related to the overestimation of the number of wet days. As a result, the intensity due to the wet days only is slightly overpredicted in these regions. This is, in turn, linked to the tendency of the RegCM3 to produce more intense and convective rainfall events in the ITCZ and the ZAB as

We compare two numerical experiments to investigate the effects of ice-phase cloud microphysical processes on simulations of wintertime precipitation in the southwestern United States. Results of these simulations, one with and the other without ice-phase microphysics, suggest that an inclusion of ice-phase microphysics plays a crucial role in simulating wintertime precipitation. The simulation that employs both the ice and water-phase microphysics better reproduced the observed spatial distribution of precipitation compared to the one without ice-phase microphysics. The most significant effect of ice-phase microphysics appeared in local production of precipitating particles by collection processes, rather than in local condensation.

Heavy rainfall events become significant in human affairs when they are combined with hydrological elements. The problem of forecasting heavyprecipitation is especially difficult since it involves making a quantitative precipitation forecast, a problem well recognized as challenging. Chennai (13.04°N and 80.17°E) faced incessant and heavy rain about 27 cm in 24 hours up to 8.30 a.m on 27th October 2005 completely threw life out of gear. This torrential rain caused by deep depression which lay 150km east of Chennai city in Bay of Bengal intensified and moved west north-west direction and crossed north Tamil Nadu and south Andhra Pradesh coast on 28th morning. In the present study, we investigate the predictability of the MM5 mesoscale model using different cumulus parameterization schemes for the heavy rainfall event over Chennai. MM5 Version 3.7 (PSU/NCAR) is run with two-way triply nested grids using Lambert Conformal Coordinates (LCC) with a nest ratio of 3:1 and 23 vertical layers. Grid sizes of 45, 15 and 5 km are used for domains 1, 2 and 3 respectively. The cumulus parameterization schemes used in this study are Anthes-Kuo scheme (AK), the Betts-Miller scheme (BM), the Grell scheme (GR) and the Kain-Fritsch scheme (KF). The present study shows that the prediction of heavy rainfall is sensitive to cumulus parameterization schemes. In the time series of rainfall, Grell scheme is in good agreement with observation. The ideal combination of the nesting domains, horizontal resolution and cloud parameterization is able to simulate the heavy rainfall event both qualitatively and quantitatively.

Extreme climate events have been increasing over much of the world, and dynamical models predict further increases in response to enhanced greenhouse forcing. We examine the ability of a high-resolution nested climate model, RegCM3, to capture the statistics of daily-scale temperature and precipitation events over the conterminous United States, using observational and reanalysis data for comparison. Our analyses reveal that RegCM3 captures the pattern of mean, interannual variability, and trend in the tails of the daily temperature and precipitation distributions. However, consistent biases do exist, including wet biases in the topographically-complex regions of the western United States and hot biases in the southern and central United States. The biases in heavyprecipitation in the western United States are associated with excessively strong surface and low-level winds. The biases in daily-scale temperature and precipitation in the southcentral United States are at least partially driven by biases in circulation and moisture fields. Further, the areas of agreement and disagreement with the observational data are not intuitive from analyzing the simulated mean seasonal temperature and precipitation fields alone. Our evaluation should enable more informed application and improvement of high-resolution climate models for the study of future changes in socially- and economically-relevant temperature and precipitation events.

The evaluation of climate model precipitation is expected to reveal biases in simulated mean and extreme precipitation which may be a result of coarse model resolution or inefficiencies in the precipitation generating mechanisms in models. The analysis of future extreme precip...

The capability to simulate the diurnal variation of precipitation over East Asia region during the summertime of 2011 is investigated using five different cumulus parameterization schemes with the Weather Research and Forecasting model. A semidiurnal cycle with a 12 h interval over land and a diurnal cycle with a 24 h interval over ocean are commonly found in all simulations, consistent with the observed diurnal cycle. Two observed dominant peaks in the early morning and afternoon are reproduced in all simulations. With overestimated precipitation rate, however, the simulated afternoon peaks occur earlier than the observed peaks by 2 h for the Kain-Fritsch (KF) and Simplified Arakawa-Schubert schemes, and by 3 h for the Betts-Miller-Janjić and Tiedtke schemes. The overestimation of simulatedprecipitation frequency leads to amplitude and phase errors in the precipitation rate, and the early peak time of simulatedprecipitation intensity intensifies the phase error in the simulation over land. The KF scheme with alternative trigger function (KFtr) based on moisture advection provides slightly better results in terms of alleviating the overestimated precipitation rate and frequency and delaying the afternoon peaks. Additional sensitivity simulations based on the change of temperature perturbation in the trigger function of the KF and KFtr schemes demonstrate the afternoon peak tends to be delayed as temperature perturbation decreases, implying the significant role of convective initiation frequency in determining diurnal peaks of precipitation. Modulation of temperature perturbation alleviates the precipitation frequency bias, while it could not resolve the precipitation intensity bias.

A recent heavyprecipitation event on 13 September 2012 and the associated landslide on 14 September 2012 is one of the most severe calamities that occurred over the Rudraprayag region in Uttarakhand, India. This heavyprecipitation event is also emblematic of the natural hazards occuring in the Himalayan region. Study objectives are to present dynamical fields associated with this event, and understand the processes related to the severe storm event, using the Weather Research and Forecasting (WRF ver 3.4) model. A triple-nested WRF model is configured over the Uttarakhand region centered over Ukhimath (30∘30'N; 79 ∘15'E), where the heavyprecipitation event is reported. Model simulation of the intense storm on 13 September 2012 is with parameterized and then with explicit convection are examined for the 3 km grid spacing domain. The event was better simulated without the consideration of convection parameterization for the innermost domain. The role of steep orography forcings is notable in rapid dynamical lifting as revealed by the positive vorticity and high reflectivity values and the intensification of the monsoonal storm. Incursion of moist air, in the lower levels, converges at the foothills of the mountains and rise along the orography to form the updraft zone of the storm. Such rapid unstable ascent leads to deep convection and increases the condensation rate of the water vapour forming clouds at a swift rate. This culminates into high intensity precipitation which leads to high amount of surface runoff over regions of susceptible geomorphology causing the landslide. Even for this intense and potentially unsual rainfall event, the processes involved appear to be the `classic' enhanced convective activity by orographic lifting of the moist air, as an important driver of the event.

The effect of effluent composition (Cl{sup {minus}}, SO{sub 4}{sup 2{minus}} or CO{sub 3}{sup 2{minus}}) on the efficiency of the hydroxide precipitation of Cu(II) modelling lime (CaO) as the precipitant has been predicted using the solubility domain approach and has been experimentally validated. Solubility domains were based on the phases that were found to be solubility-limiting for systems representing potential effluent chemical composition limits. The generated solubility domains generally encompassed the experimentally observed solubilities, thereby providing effluent treatment quality assurance ranges for the hydroxide precipitation process. The presence of gypsum (CaSO{sub 4{center_dot}}2H{sub 2}O) and calcite (CaCO{sub 3}) as secondary precipitates had little effect on the observed residual Cu(II) solubilities, with Cu(II) mobility being governed by the least-soluble kinetically precipitated (rather than thermodynamically favored) phase in the system under study.

This study analyzes the uncertainty of seasonal (winter and summer) precipitation extremes as simulated by a recent version of the Canadian Regional Climate Model (CRCM) using 16 simulations (1961-1990), considering four sources of uncertainty from: (a) the domain size, (b) the driving Atmosphere-Ocean Global Climate Models (AOGCM), (c) the ensemble member for a given AOGCM and (d) the internal variability of the CRCM. These 16 simulations are driven by 2 AOGCMs (i.e. CGCM3, members 4 and 5, and ECHAM5, members 1 and 2), and one set of re-analysis products (i.e. ERA40), using two domain sizes (AMNO, covering all North America and QC, a smaller domain centred over the Province of Québec). In addition to the mean seasonal precipitation, three seasonal indices are used to characterize different types of variability and extremes of precipitation: the number of wet days, the maximum number of consecutive dry days, and the 95th percentile of daily precipitation. Results show that largest source of uncertainty in summer comes from the AOGCM selection and the choice of domain size, followed by the choice of the member for a given AOGCM. In winter, the choice of the member becomes more important than the choice of the domain size. Simulated variance sensitivity is greater in winter than in summer, highlighting the importance of the large-scale circulation from the boundary conditions. The study confirms a higher uncertainty in the simulatedheavy rainfall than the one in the mean precipitation, with some regions along the Great Lakes—St-Lawrence Valley exhibiting a systematic higher uncertainty value.

Strengthening and toughening by interfacial precipitation are strongly connected with crack bowing and deflection. In the present study, three dimensional numerical simulation of these events was performed on ceramics particulate glass matrix composites with interfacial precipitation by calculating the equations for a crack bowing and deflection. This numerical simulation revealed that fracture toughness and strength increased with the addition of interfacial precipitation because a crack bowing emerged. These results are in agreement with experimental data for fracture toughness.

Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by

In the morning of the 18th of February 2008 Lisbon and Setúbal were under the influence of a heavy rain event associated to a cut-off low formed in southern Azores between the 14th and 15th of February. The total daily precipitation record was exceeded in the 18th of February at Lisboa/Geofísico station; 36 mm of precipitation were registered between 4 and 5 a.m., whereas in Setúbal 60 mm were recorded during one hour (between 11 and 12 a.m.), of the same day. These two cities are located near the mouth of Tagus and Sado rivers, respectively, running to the Atlantic Ocean, and both have experience severe floods. The present work will present the sensitivity of the Weather Research and Forecasting (WRF) model to different geometric model configurations and physical parametrisations, and to data assimilation procedures for the same grid resolution and physical parametrisations. The WRF model is running in operational mode for Portugal at the University of Aveiro in two different horizontal and vertical resolution and physical set of parametrisations, driven by the Global Forecast System (GFS) forecasts. The first configuration (OP1) is shown in http://climetua.fis.ua.pt/main/otempo.php?lang=pt and consists of two nested domains and 27 vertical levels, the coarsest domain (25 km) covering the Iberian Peninsula and part of the East Atlantic and the finer grid domain (5 km) covering Portugal. For the second configuration (OP2) (shown in http://www2.fis.ua.pt/torre/luis/), the outer and inner domains have a horizontal resolution of 21 and 7 km, respectively. The physics parametrisation of the two operational designs differ on the microphysics and cumulus schemes, and on the applied land surface model, which are named respectively for: (i) OP1 - WSM 6 class graupel microphysics scheme, Grell-Devenyi ensemble cumulus scheme and Unified Noah land-surface model; (ii) OP2 - Ferrier microphysics scheme, Kain-Fritsch cumulus scheme and Thermal diffusion land-surface model

A daily stochastic spatiotemporal precipitation generator that yields spatially consistent gridded quantitative precipitation realizations is described. The methodology relies on a latent Gaussian process to drive precipitation occurrence and a probability integral transformed Gaussian process for intensity. At individual locations, the model reduces to a Markov chain for precipitation occurrence and a gamma distribution for precipitation intensity, allowing statistical parameters to be included in a generalized linear model framework. Statistical parameters are modeled as spatial Gaussian processes, which allows for interpolation to locations where there are no direct observations via kriging. One advantage of such a model for the statistical parameters is that stochastic generator parameters are immediately available at any location, with the ability to adapt to spatially varying precipitation characteristics. A second advantage is that parameter uncertainty, generally unavailable with deterministic interpolators, can be immediately quantified at all locations. The methodology is illustrated on two data sets, the first in Iowa and the second over the Pampas region of Argentina. In both examples, the method is able to capture the local and domain aggregated precipitation behavior fairly well at a wide range of time scales, including daily, monthly, and annually.

Precipitation is arguably one of the most important forcing variables that drive terrestrial water cycle processes. The process of precipitation exhibits significant variability in space and time, is associated with different water phases (liquid or solid) and depends on several other factors (aerosols, orography etc), which make estimation and modeling of this process a particularly challenging task. As such, precipitation information from different sensors/products is associated with uncertainty. Propagation of this uncertainty into hydrologic simulations can have a considerable impact on the accuracy of the simulated hydrologic variables. Therefore, to make hydrologic predictions more useful, it is important to investigate and assess the impact of precipitation uncertainty in hydrologic simulations in order to be able to quantify it and identify ways to minimize it. In this work we investigate the impact of precipitation uncertainty in hydrologic simulations using land surface models (e.g. ORCHIDEE) and global hydrologic models (e.g. WaterGAP3) for the simulation of several hydrologic variables (soil moisture, ET, runoff) over the Iberian Peninsula. Uncertainty in precipitation is assessed by utilizing various sources of precipitation input that include one reference precipitation dataset (SAFRAN), three widely-used satellite precipitation products (TRMM 3B42v7, CMORPH, PERSIANN) and a state-of-the-art reanalysis product (WFDEI) based on the ECMWF ERA-Interim reanalysis. Comparative analysis is based on using the SAFRAN-simulations as reference and it is carried out at different space (0.5deg or regional average) and time (daily or seasonal) scales. Furthermore, as an independent verification, simulated discharge is compared against available discharge observations for selected major rivers of Iberian region. Results allow us to draw conclusions regarding the impact of precipitation uncertainty with respect to i) hydrologic variable of interest, ii

The Indianapolis region exhibits a precipitation distribution indicative of urban weather modification: negative bias upwind and positive bias downwind. The causes for such a distribution within an urban area arise from a combination of land-surface heterogeneity and urban aerosol-cloud interaction. This study investigates the causes of the precipitation distribution with a 120-day simulation using the Regional Atmospheric Modeling System (RAMS) coupled with the Town Energy Budget (TEB) model. Using a nested grid with a maximum resolution of 500m, a seasonal simulation of May through August, 2008 is conducted. Land surface conditions are varied, removing, expanding, and intensifying the Indianapolis urban area. Aerosol conditions are scaled by a three-dimensional combination of MODIS and CALIPSO observations, and varied in concentration and plume extent. Results from the study demonstrate the paradigm of urban precipitation modification on a seasonal time scale. The boundary between the rural and urban land surfaces weakens approaching systems upwind, decreasing precipitation in the city center. A larger urban extent diminishes the systems further. The aerosol plume downwind increases cloud lifetimes via cloud-nucleating aerosol, then invigorates precipitation via large drizzle-invigorating aerosols. The overall effect reproduces the observed negative precipitation bias upwind and positive bias downwind of the urban center. A lower concentration of aerosols leads to a higher proportion of stratiform rain over a larger area, whereas a higher concentration of aerosols leads to more convective rain and heavy rain events. This manifests in a weekly cycle of precipitation with rain most likely on weekends, and with less frequent but heavier rain events most likely during midweek, when aerosol concentrations are the highest. More intense urbanization, via both land surface and aerosol effects, creates more frequent heavy rainfall events and exacerbates dry

Reasonably modeling the magnitude, south-north gradient and seasonal propagation of precipitation associated with the East Asian Summer Monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain-Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulatedprecipitation and surface energy features are generally improved.more » The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulatedprecipitation condensational heating, the monsoon circulations are also improved. Lastly, by using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.« less

Reasonably modeling the magnitude, south-north gradient and seasonal propagation of precipitation associated with the East Asian Summer Monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain-Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulatedprecipitation and surface energy features are generally improved. The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulatedprecipitation condensational heating, the monsoon circulations are also improved. Lastly, by using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.

Reasonably modeling the magnitude, south-north gradient and seasonal propagation of precipitation associated with the East Asian summer monsoon (EASM) is a challenging task in the climate community. In this study we calibrate five key parameters in the Kain-Fritsch convection scheme in the WRF model using an efficient importance-sampling algorithm to improve the EASM simulation. We also examine the impacts of the improved EASM precipitation on other physical process. Our results suggest similar model sensitivity and values of optimized parameters across years with different EASM intensities. By applying the optimal parameters, the simulatedprecipitation and surface energy features are generally improved. The parameters related to downdraft, entrainment coefficients and CAPE consumption time (CCT) can most sensitively affect the precipitation and atmospheric features. Larger downdraft coefficient or CCT decrease the heavy rainfall frequency, while larger entrainment coefficient delays the convection development but build up more potential for heavy rainfall events, causing a possible northward shift of rainfall distribution. The CCT is the most sensitive parameter over wet region and the downdraft parameter plays more important roles over drier northern region. Long-term simulations confirm that by using the optimized parameters the precipitation distributions are better simulated in both weak and strong EASM years. Due to more reasonable simulatedprecipitation condensational heating, the monsoon circulations are also improved. By using the optimized parameters the biases in the retreating (beginning) of Mei-yu (northern China rainfall) simulated by the standard WRF model are evidently reduced and the seasonal and sub-seasonal variations of the monsoon precipitation are remarkably improved.

Subsurface radionuclide and trace metal contaminants throughout the U.S. Department of Energy (DOE) complex pose one of DOE’s greatest challenges for long-term stewardship. One promising in situ immobilization approach of these contaminants is engineered mineral (co)precipitation of calcite driven by urea hydrolysis that is catalyzed by enzyme urease. The tight nonlinear coupling among flow, transport, reaction and reaction-induced property changes of media of this approach was studied by reactive transport simulations with systematically increasing level of complexities of reaction network and physical/chemical heterogeneities using a numerical simulator named STOMP. Sensitivity studies on the reaction rates of both urea hydrolysis and calcite precipitation are performed via controlling urease enzyme concentration and precipitation rate constant according to the rate models employed. We have found that the rate of ureolysis is a dominating factor in the amount of precipitated mineral; however, the spatial distribution of the precipitates depends on both rates of ureolysis and calcite precipitation. A maximum 5% reduction in the porosity was observed within the simulation time period of 6 pore volumes in our 1-dimensional (1D) column simulations. When a low permeability inclusion is considered in the 2D simulations, the altered flow fields redistribute mineral forming constituents, leading to a distorted precipitation reaction front. The simulations also indicate that mineral precipitation occurs along the boundary of the low permeability zone, which implies that contaminants in the low permeability zone could be encapsulated and isolated from the flow paths.

In this paper, a PV-gradient related parameter-the second-order potential vorticity (SPV) is generalized into a non-uniformly saturated atmosphere to involve the PV-gradient into precipitation diagnosis, assuming that PV gradient is more capable of describing the whole structure of the air mass boundaries than other single element gradients. The newly derived second-order moist potential vorticity (SMPV), which is defined as the dot product of the generalized vorticity vector and three-dimensional gradient of a conserved form of generalized potential vorticity (GPV), keeps the conserved property as SPV in the frictionless, moist adiabatic atmosphere. Nevertheless, due to the complex calculation of SMPV, a non-conservative form of SMPV (NSMPV) is subtracted from SMPV, which is defined as the dot product of vorticity vector and three-dimensional gradient of GPV by involving the baroclinic vorticity. The capability of the NSMPV on diagnosing and detecting heavyprecipitation is examined for a heavy rainfall case, with GPV as a comparison. A typical scale analyses in this case shows that GPV is mainly a coupling of static stability and vertical vorticity, while NSMPV contains static stability, vorticity enstrophy and their vertically inhomogeneity. Due to these information, both GPV and NSMPV show strong anomalies over the precipitation region, by reflecting the cyclonic shear and large vertical variations of temperature and humidity in the lower troposphere. However, GPV also appears strong, wide anomalies out of the precipitation region while NSMPV does not. In addition, due to the vertical gradient of vorticity enstrophy and static stability contained in NSMPV, it also has a reflection on the invasion of cold, dry air in the near-surface layer, which is seen to be a triggering mechanism of the strong precipitation. This indicates that NSMPV perform better than GPV in detecting heavy rainfall and are powerful on distinguishing between precipitation and non-precipitation

Operational quantitative precipitation forecasts (QPF) are provided routinely by weather services or hydrological authorities, particularly those responsible for densely populated regions of small catchments, such as those typically found in Mediterranean areas prone to flash-floods. Specific rainfall values are used as thresholds for issuing warning levels considering different time frameworks (mid-range, short-range, 24h, 1h, etc.), for example 100 mm in 24h or 60 mm in 1h. There is a clear need to determine how feasible is a specific rainfall value for a given lead-time, in particular for very short range forecasts or nowcasts typically obtained from weather radar observations (Pierce et al 2012). In this study we assess which specific nowcast lead-times can be provided for a number of heavyprecipitation events (HPE) that affected Catalonia (NE Spain). The nowcasting system we employed generates QPFs through the extrapolation of rainfall fields observed with weather radar following a Lagrangian approach developed and tested successfully in previous studies (Berenguer et al. 2005, 2011).Then QPFs up to 3h are compared with two quality controlled observational data sets: weather radar quantitative precipitation estimates (QPE) and raingauge data. Several high-impact weather HPE were selected including the 7 September 2005 Llobregat Delta river tornado outbreak (Bech et al. 2007) or the 2 November 2008 supercell tornadic thunderstorms (Bech et al. 2011) both producing, among other effects, local flash floods. In these two events there were torrential rainfall rates (30' amounts exceeding 38.2 and 12.3 mm respectively) and 24h accumulation values above 100 mm. A number of verification scores are used to characterize the evolution of precipitation forecast quality with time, which typically presents a decreasing trend but showing an strong dependence on the selected rainfall threshold and integration period. For example considering correlation factors, 30

On 21 September 2010, heavy rainfall with a local maximum of 259 mm d-1 occurred near Seoul, South Korea. We examined the ability of the Weather Research and Forecasting (WRF) model in reproducing this disastrous rainfall event and identified the role of two physical processes: planetary boundary layer (PBL) and microphysics (MPS) processes. The WRF model was forced by 6-hourly National Centers for Environmental Prediction (NCEP) Final analysis (FNL) data for 36 hours form 1200 UTC 20 to 0000 UTC 22 September 2010. Twenty-five experiments were performed, consisting of five different PBL schemes—Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ), Quasi Normal Scale Elimination (QNSE), Bougeault and Lacarrere (BouLac), and University of Washington (UW)—and five different MPS schemes—WRF Single-Moment 6-class (WSM6), Goddard, Thompson, Milbrandt 2-moments, and Morrison 2-moments. As expected, there was a specific combination of MPS and PBL schemes that showed good skill in forecasting the precipitation. However, there was no specific PBL or MPS scheme that outperformed the others in all aspects. The experiments with the UW PBL or Thompson MPS scheme showed a relatively small amount of precipitation. Analyses form the sensitivity experiments confirmed that the spatial distribution of the simulatedprecipitation was dominated by the PBL processes, whereas the MPS processes determined the amount of rainfall. It was also found that the temporal evolution of the precipitation was influenced more by the PBL processes than by the MPS processes.

This Tech Report summarizes years of study and experiences on using GOES Water vapor (6.7 micron and precipitable water) and Special Sensor Microwave Imager (SSM/1) from the Defense Meteorological Satellite Program (DMSP) derived Precipitable Water (PNAI) for detecting environments favorable for convectively produced flash floods. An emphasis is on the moisture. upper air flow, and equivalent potential temperature (Theta(sub e)) patterns that lead to devastating flood events. The 15 minute 6.7 micron water vapor imagery is essential for tracking middle to upper tropospheric disturbances that produce upward vertical motion and initiate flash flood producing systems. Water vapor imagery at 6.7 micron is also used to detect surges of upper level moisture (called tropical water vapor plumes) that have been associated with extremely heavy rainfall. Since the water vapor readily depicts lifting mechanisms and upper level moisture, water vapor imagery is often an excellent source of data for recognizing patterns of heavyprecipitation and flash floods. In order to analyze the depth of the moisture, the PW aspects of the troposphere must be measured. The collocation (or nearby location) of high values ofP\\V and instability are antecedent conditions prior to the flash flood or heavy rainfall events. Knowledge of PW magnitudes have been used as thresholds for impending flash flood events, PW trends are essential in flash flood prediction. Conceptual models and water vapor products are used to study some of the characteristics of convective systems that occurred over the United States of America (USA) during the summer of 1997 and the 1997-1998 El Nino. P\\V plumes were associated with most of the \\vest coast heavyprecipitation events examined during the winter season of 1997 - 1998, In another study, conducted during the summer season of 1997. results showed that the collocation of water vapor (6.7 micron) and P\\N' plumes possessed higher correlations with predicted

The northern coast of the Iberian Peninsula is one of the wettest areas of Europe. Most of the coastal observatories receive exceed 1000mm, and the rainfall is higher than 1700mm along the basque coast. The contribution of late summer-early fall precipitation is remarkable (about 25 %), unusual taking in account the southern latitude of the region at continental scale (Cfb climate, following Köppen’s notation). One of the causes of this summertime wetness are the frequent heavy rainfall events, historically responsible of the most damaging floods in the region. The aim of this paper is to identify and investigate the spatial and temporal characteristics of those heavy rain events, improving the understanding of the dynamical mechanisms by means of a classification of the related atmospheric patterns. The role of the exchange of heat fluxes from a very warm pool of water around the vertex of the Gulf of Biscay, feeding the lowest atmospheric layers, is also discussed. Heavy rainfall events were analyzed using long-term daily rainfall records from 22 stations belonging to the spanish, portuguese and french meteorological networks. The 1000 hPa and 500 hPa geopotential heights (hereafter Z1000 and Z500), as well as the 850 hPa temperature (T850) were utilized to derive a typology of circulation pattern, combining principal components analysis (PCA) and cluster analysis (CA). Results show that most of those heavyprecipitation events, whose atmospheric environment and spatial impacts remember some of the typical features of the heavyprecipitation events in the Spanish Mediterranean coast, implicate convective systems, associated to upper level stationary disturbances ("cold lows"), which trigger a thermodynamic instability. Most of them affect a relatively restricted area, from Cantabria to the Basque Country, and, even within this area, most of the precipitation falls in the shorelines and the first orographic ridges. Finally, it is worth to mention that the

The heavy-ion fusion (HIF) community recently developed a power-plant design that meets the various requirements of accelerators, final focus, chamber transport, and targets. The point design is intended to minimize physics risk and is certainly not optimal for the cost of electricity. Recent chamber-transport simulations, however, indicate that changes in the beam ion species, the convergence angle, and the emittance might allow more-economical designs.

We evaluate the effects of spatial resolution on the ability of a regional climate model to reproduce observed extreme precipitation for a region in the Southwestern United States. A total of 73 National Climate Data Center observational sites spread throughout Arizona and New Mexico are compared with regional climate simulations at the spatial resolutions of 50 km and 10 km for a 31 year period from 1980 to 2010. We analyze mean, 3-hourly and 24-hourly extreme precipitation events using WRF regional model simulations driven by NCEP-2 reanalysis. The mean climatological spatial structure of precipitation in the Southwest is well represented by the 10 km resolution but missing in the coarse (50 km resolution) simulation. However, the fine grid has a larger positive bias in mean summer precipitation than the coarse-resolution grid. The large overestimation in the simulation is in part due to scale-dependent deficiencies in the Kain-Fritsch convective parameterization scheme that generate excessive precipitation and induce a slow eastward propagation of the moist convective summer systems in the high-resolution simulation. Despite this overestimation in the mean, the 10 km simulation captures individual extreme summer precipitation events better than the 50 km simulation. In winter, however, the two simulations appear to perform equally in simulating extremes.

Mine water from a precious metal mine in Colorado drains into an underground tunnel and flows for about 8 km before being discharged into a series of sequentially connected settling ponds (5) aimed at removing suspended particulate. Our results suggest these ponds also remove heavy metals from solution through adsorption and mineral precipitation. Analyses of the precipitates and water in the settling ponds showed relatively higher metal concentration on the precipitates than in the corresponding aqueous solutions. Speciation modeling showed that the precipitates were mainly travertine, ferrihydrite, fe-oxyhdroxide and gypsum and these are expected to provide surfaces for metal adsorption. Overall, the average concentrations of trace metals were such that, Al concentration was 0.0 mg/L for the aqueous sample and 9.4 mg/L for the precipitate; Fe concentration was 0.04 mg/L for the aqueous sample and 20.1 mg/L for the precipitate; Mn concentration was 0.2 mg/L for the aqueous sample and 10.2 mg/L for the precipitate; Sr concentration was 3 mg/L for the aqueous sample and 8 mg/L for the precipitate; Zn concentration was 0.1 mg/L for the aqueous sample and 1.4 mg/L for the precipitate. Sulfate concentrations in solutions (1346 mg/L) were about seventeen times higher than on the precipitate (80 mg/L). As the water exits the tunnel, its carbon is expected to consistently decrease over space as it moves along the settling ponds while precipitating carbonates. The dissolved inorganic carbon (DIC) concentrations showed consistent drop from 109 mg/L at the tunnel exit to 96 mg/L at middle pond and 92 mg/L at the exit pond, which corresponds to decreasing pCO2 and removal of carbon from solution through travertine precipitation and CO2 outgassing. This data indicate a strong influence of mineral precipitate as an effective component in the attenuation of metals in mine

A fingering instability can develop at the interface between two fluids when the more mobile fluid is injected into the less-mobile one. For example, viscous fingering appears when a less viscous (i.e., more mobile) fluid displaces a more viscous (and hence less mobile) one in a porous medium. Fingering can also be due to a local change in mobility arising when a precipitation reaction locally decreases the permeability. We numerically analyze the properties of the related precipitation fingering patterns occurring when an A +B →C chemical reaction takes place, where A and B are reactants in solution and C is a solid product. We show that, similarly to reactive viscous fingering patterns, the precipitation fingering structures differ depending on whether A invades B or vice versa. This asymmetry can be related to underlying asymmetric concentration profiles developing when diffusion coefficients or initial concentrations of the reactants differ. In contrast to reactive viscous fingering, however, precipitation fingering patterns appear at shorter time scales than viscous fingers because the solid product C has a diffusivity tending to zero which destabilizes the displacement. Moreover, contrary to reactive viscous fingering, the system is more unstable with regard to precipitation fingering when the high-concentrated solution is injected into the low-concentrated one or when the faster diffusing reactant displaces the slower diffusing one.

We investigate the sensitivity of simulated cloud properties and surface precipitation to assumptions regarding the size distributions of the precipitating hydrometeors in a one-moment bulk microphysics scheme. Three sensitivity experiments were applied to two composites of 15 convective and 15 frontal stratiform intense precipitation events observed in a coastal midlatitude region (Belgium), which were evaluated against satellite-retrieved cloud properties and radar-rain-gauge derived surface precipitation. It is found that the cloud optical thickness distribution was well captured by all experiments, although a significant underestimation of cloudiness occurred in the convective composite. The cloud-top-pressure distribution was improved most by more realistic snow size distributions (including a temperature-dependent intercept parameter and non-spherical snow for the calculation of the slope parameter), due to increased snow depositional growth at high altitudes. Surface precipitation was far less sensitive to whether graupel or hail was chosen as the rimed ice species, as compared to previous idealized experiments. This smaller difference in sensitivity could be explained by the stronger updraught velocities and higher freezing levels in the idealized experiments compared to typical coastal midlatitude environmental conditions.

investigate the scaling between precipitation and temperature changes in warm and cold climates using six models that have simulated the response to both increased CO2 and Last Glacial Maximum (LGM) boundary conditions. Globally, precipitation increases in warm climates and decreases in cold climates by between 1.5%/°C and 3%/°C. Precipitation sensitivity to temperature changes is lower over the land than over the ocean and lower over the tropical land than over the extratropical land, reflecting the constraint of water availability. The wet tropics get wetter in warm climates and drier in cold climates, but the changes in dry areas differ among models. Seasonal changes of tropical precipitation in a warmer world also reflect this "rich get richer" syndrome. Precipitation seasonality is decreased in the cold-climate state. The simulated changes in precipitation per degree temperature change are comparable to the observed changes in both the historical period and the LGM.

Stochastic weather generators are frequently used in climate change studies to simulate input to hydrologic models. In this presentation, we focus on the particular problem of simulating daily precipitation at multiple stations in a region for which records are available. Daily precipitation is a highly intermittent process, highly variable in space, and typically has a highly skewed distribution. A stochastic precipitation model should ideally preserve the regional pattern of intermittence, the autocorrelation, the cross-correlation, and the marginal distributions of observed precipitation. For this purpose, we employed a multivariate autoregressive model. Below zero-values were considered days with no rain. To preserve the marginal distributions of observed precipitation at different stations some prior transformation of data was required. The presentation will describe the experience gained from applying the model to precipitation records in Canada. Focus will be on analytical model properties, methods of parameter estimation, and the preservation of observed statistics in the application.

Reproducibility of diurnal precipitation over northern Eurasia simulated by CMIP5 climate models in their historical runs were evaluated, in comparison with station data (NCDC-9813) and satellite data (GSMaP-V5). We first calculated diurnal cycles by averaging precipitation at each local solar time (LST) in June-July-August during 1981-2000 over the continent of northern Eurasia (0-180E, 45-90N). Then we examined occurrence time of maximum precipitation and a contribution of diurnally varying precipitation to the total precipitation.The contribution of diurnal precipitation was about 21% in both NCDC-9813 and GSMaP-V5. The maximum precipitation occurred at 18LST in NCDC-9813 but 16LST in GSMaP-V5, indicating some uncertainties even in the observational datasets. The diurnal contribution of the CMIP5 models varied largely from 11% to 62%, and their timing of the precipitation maximum ranged from 11LST to 20LST. Interestingly, the contribution and the timing had strong negative correlation of -0.65. The models with larger diurnal precipitation showed precipitation maximum earlier around noon. Next, we compared sensitivity of precipitation to surface temperature and tropospheric humidity between 5 models with large diurnal precipitation (LDMs) and 5 models with small diurnal precipitation (SDMs). Precipitation in LDMs showed high sensitivity to surface temperature, indicating its close relationship with local instability. On the other hand, synoptic disturbances were more active in SDMs with a dominant role of the large scale condensation, and precipitation in SDMs was more related with tropospheric moisture. Therefore, the relative importance of the local instability and the synoptic disturbances was suggested to be an important factor in determining the contribution and timing of the diurnal precipitation. Acknowledgment: This study is supported by Green Network of Excellence (GRENE) Program by the Ministry of Education, Culture, Sports, Science and Technology

A computer program to simulate hybrid and electric advanced vehicle systems (HEAVY) is described. It is intended for use early in the design process: concept evaluation, alternative comparison, preliminary design, control and management strategy development, component sizing, and sensitivity studies. It allows the designer to quickly, conveniently, and economically predict the performance of a proposed drive train. The user defines the system to be simulated using a library of predefined component models that may be connected to represent a wide variety of propulsion systems. The development of three models are discussed as examples.

Watershed models are used for simulating basin streamflows based on spatially sparse precipitation and temperature observations. The sparse observations are typically interpolated on a regular grid or a subbasin as inputs to the hydrologic models. Given the paucity in observations and nonhomogenous nature of the precipitation process, differences in interpolation methods can potentially impact the simulated streamflow. Of course, hydrologic model parameter uncertainty also contribute to the errors, but in this paper we focus on the uncertainty due to interpolation methods. To this end, first we developed a two-step process in which the precipitation occurrence is first generated via a logistic regression model, and the amounts are then estimated using a Multiple Linear Regression (MLR) and Locally Weighted Polynomial Regression (LWP). The two-step approach is shown to capture the spatial variability of precipitation effectively than other competing traditional methods. Secondly, interpolated precipitation estimates are input into the watershed model, Precipitation Runoff Modeling System (PRMS) to estimate daily and consequently, monthly and seasonal streamflows. Streamflow estimates from PRMS are obtained for three methods of precipitation interpolation, MLR, LWP and the currently used method in PRMS, Climatological MLR (CMLR). Streamflows are compared on a variety of attributes. We find that the MLR and LWP methods perform much better in simulating the streamflows compared to CMLR. Ensembles of precipitation from the two methods (MLR and LWP) coupled with the logistic regression for precipitation occurrence, are generated to subsequently generate ensembles of streamflows from the watershed model. This approach captures the input uncertainty.

Several major flood events occurred in Germany in the past 15-20 years especially in the eastern parts along the rivers Elbe and Danube. Examples include the major floods of 2002 and 2013 with an estimated loss of about 2 billion Euros each. The last major flood events in the State of Baden-Württemberg in southwest Germany occurred in the years 1978 and 1993/1994 along the rivers Rhine and Neckar with an estimated total loss of about 150 million Euros (converted) each. Flood hazard originates from a combination of different meteorological, hydrological and hydraulic processes. Currently there is no defined methodology available for evaluating and quantifying the flood hazard and related risk for larger areas or whole river catchments instead of single gauges. In order to estimate the probable maximum loss for higher return periods (e.g. 200 years, PML200), a stochastic model approach is designed since observational data are limited in time and space. In our approach, precipitation is linearly composed of three elements: background precipitation, orographically-induces precipitation, and a convectively-driven part. We use linear theory of orographic precipitation formation for the stochastic precipitation model (SPM), which is based on fundamental statistics of relevant atmospheric variables. For an adequate number of historic flood events, the corresponding atmospheric conditions and parameters are determined in order to calculate a probability density function (pdf) for each variable. This method involves all theoretically possible scenarios which may not have happened, yet. This work is part of the FLORIS-SV (FLOod RISk Sparkassen Versicherung) project and establishes the first step of a complete modelling chain of the flood risk. On the basis of the generated stochastic precipitation event set, hydrological and hydraulic simulations will be performed to estimate discharge and water level. The resulting stochastic flood event set will be used to quantify the

A broadband electron (BBE) precipitation model is implemented and analyzed in the MI coupling module of the Lyon-Fedder-Mobarry MHD simulation. Both number flux and energy flux of precipitating BBEs are regulated by MHD variables calculated near the low-altitude boundary of the LFM simulation. An empirical relation deduced from results of Keiling et al. (2003) is used to relate the AC Poynting flux to the energy flux precipitating BBEs in the simulation. We are investigating two different ways of regulating the number flux of BBE precipitation, one using an empirical relation between AC Poynting flux and number flux (Strangeway, unpublished) and another by constraining the intensity and cut-off energy of a fixed-pitch angle distribution of BBEs in terms of MHD simulation variables. The contributions to ionospheric conductance from BBE precipitation are evaluated using empirical relations derived by Robinson et al. (1987). The BBE-induced-conductance is added to the “standard” auroral contribution to conductance derived from monoenergetic and diffuse electron precipitation in the existing LFM precipitation model. The simulation is driven by ideal SW/IMF conditions with Vsw=400 km/s, Nsw=5/cc and Bz=-5 nT. The simulated time-average AC Poynting flux pattern resembles statistical patterns from Polar data (Keiling et al. 2003), and the simulated statistical pattern of BBE number flux resembles the statistical maps derived from DMSP data (Newell et al. 2009) on the nightside with a similar dawn-dusk asymmetry. The ionospheric Pedersen and Hall conductances are enhanced about 20% by the BBE precipitation. The number flux produced by BBEs is the same order of magnitude as that of monoenergetic and diffuse electrons. We thus expect BBE precipitation to have a moderate effect on the E-region ionosphere and a more significant influence on the density distribution of the F-region ionosphere.

Coordinated analysis of the "Bison Pool" (BP) Environmental Genome and a complementary contextual geochemical dataset of ~75 parameters revealed biogeochemical cycling and metabolic and microbial community shifts in a Yellowstone National Park hot spring ecosystem (1). The >22m outflow of BP is a gradient of decreasing temperature, increasing dissolved oxygen, and changing availability of nutrients. Microbial life at BP transitions from a 92°C chemosynthetic community in the BP source pool to a 56°C photosynthetic mat community. Metagenomic data at BP showed the potential for both heterotrophic and autotrophic carbon metabolism (rTCA and acetyl-CoA cycles) in the highest temperature, chemosynthetic regions (1). This region of the outflow is dominated by Aquificales and Pyrococcus relatives, with smaller contributions of heterotrophic Bacteria. Following a 2h heavyprecipitation event we observed an influx of exogenous organic material into the source pool supplied from the meadow surrounding the BP area. We sampled biomass and fluid at several locations within the outflow immediately following the event, and on several occasions for the next eight days. Elemental analysis and carbon and nitrogen isotopic analyses were conducted on biomass and sediment, and dissolved organic and inorganic carbon content and δ13C of fluids were analyzed. DNA and RNA were extracted, and following RT-PCR, nitrogen cycle functional gene expression was evaluated. Previous work at BP has shown that chemosynthetic biomass may carry isotopic signatures of fractionation during carbon fixation, via the acetyl-CoA and rTCA cycles (2). However, the addition of exogenous organic carbon during the rain event had an immediate and dramatic effect on the sediments and biofilms in the chemosynthetic zone of the outflow. Dissolved organic carbon was the highest measured in six years. Chemosynthetic biomass responded by incorporating the organic carbon. Carbon isotopic signatures in chemosynthetic

The nonlinear coupling of fluid flow, reactive chemical transport and pore structure changes due to mineral precipitation (or dissolution) in porous media play a key role in a wide variety of processes of scientific interest and practical importance. Significant examples include the evolution of fracture apertures in the subsurface, acid fracturing stimulation for enhanced oil recovery and immobilizations of radionuclides and heavy metals in contaminated groundwater. We have developed a pore-scale simulation technique for modeling coupled reactive flow and structure evolution in porous media and fracture apertures. Advection, diffusion, and mineral precipitation resulting in changes in pore geometries are treated simultaneously by solving fully coupled fluid momentum and reactive solute transport equations. In this model, the reaction-induced evolution of solid grain surfaces is captured using a level set method. A sub-grid representation of the interface, based on the level set approach, is used instead of pixel representations of the interface often used in cellular-automata and most lattice-Boltzmann methods. The model is validated against analytical solutions for simplified geometries. Precipitation processes were simulated under various flow conditions and reaction rates, and the resulting pore geometry changes are discussed. Quantitative relationships between permeability and porosity under various flow conditions and reaction rates are reported.

Evidence for auroral particle precipitation at Jupiter was provided by the ultraviolet spectrometers onboard the Voyagers 1 and 2 spacecraft and by the International Ultraviolet Explorer (IUE). Magnetospheric measurements made by instruments onboard the Voyager spacecraft show that energetic sulfur and oxygen ions are precipitating into the upper atmosphere of Jupiter. A theoretical model has been constructed describing the interaction of precipitating oxygen with the Jovian atmosphere. The auroral energy is deposited in the atmosphere by means of ionization, excitation, and dissociation and heating of the atmospheric gas. Energetic ion and electron precipitation are shown to have similar effects on the atmosphere and ionosphere of Jupiter.

The Met Office 1.5-km UKV convective-permitting models (CPM) is used to downscale present-climate and RCP8.5 60-km HadGEM3 GCM simulations. Extreme UK hourly precipitation intensities increase with local near-surface temperatures and humidity; for temperature, the simulated increase rate for the present-climate simulation is about 6.5% K**-1, which is consistent with observations and theoretical expectations. While extreme intensities are higher in the RCP8.5 simulation as higher temperatures are sampled, there is a decline at the highest temperatures due to circulation and relative humidity changes. Extending the analysis to the broader synoptic scale, it is found that circulation patterns, as diagnosed by MSLP or circulation type, play an increased role in the probability of extreme precipitation in the RCP8.5 simulation. Nevertheless for both CPM simulations, vertical instability is the principal driver for extreme precipitation.

The role of aerosols in nonlinear feedbacks on atmospheric processes is in a focus of many researches. Particularly, the importance of black carbon particles for evolution of physical weather including precipitation formation and release is investigated by numerical modelling as well as observation networks. However, certain discrepancies between results obtained by different methods are remained. The increasing of complexity in numerical weather modelling systems leads to enlarging a volume of output data and promises to reveal new aspects in complexity of interactions and feedbacks. The Harmonie-38h1.2 model with the AROME physical package is used to study changes in precipitation life-cycle under black carbon polluted conditions. A model configuration includes a radar data assimilation procedure on a high resolution domain covering the Scandinavia region. Model results show that precipitation rate and distribution as well as other variables of atmospheric dynamics and physics over the domain are sensitive to aerosol concentrations. The attention should also be paid to numerical aspects, such as a list of observation types involved in assimilation. The use of high resolution radar information allows to include mesoscale features in initial conditions and to decrease the growth rate of a model error with the lead time.

Increases in land surface temperature will have a significant affect on the hydrological cycle, particularly in regions where the available water resources are mainly dominated by the melting snow or ice. Thus, to clarify the impact of climate change on river discharge in cold and mountainous region is becoming one of the urgent issues for policy making and planning for the integrated river water management under the inevitable warming climate. However, in order to study climate change impacts on water resources in the heavy snow region, snow-melt runoff simulation for dam reservoir should be improved. Because, the available meteorological data for runoff simulation is quite limited, especially in a mountainous regions in Japan. In this study, we analyzed the inflow into the Okutadami Dam in the Agano River basin located in the northern mountainous region in Japan by a distributed hydrological model (Hydro-BEAM: Hydrological river Basin Environment Assessment Model). The Okutadami dam has an important role as one of the largest hydro-power generation dam in Japan. The result of our initial simulation underestimated the inflow significantly, especially in snow melting season, because of small input precipitation. We firstly modified the input precipitation by the JMA (Japan Meteorological Agency)'s climatic value 2010 (monthly 1km2 averaged mesh based precipitation dataset during the period from 1981 to 2010). Due to the modification, simulated annual mean river discharge (water balance) was improved significantly. Secondly, we modified the threshold temperature which distinguishes rainfall and snowfall improved the reproducibility slightly. Lastly, we modified the monthly discharge variation (seasonal change pattern) in snow melting period by considering the effect of heat supply by rainfall on snow surface layer. Consequently, we found that the calculated inflow to the Okutadami dam agreed well the observation. These methods will contribute to clarify the

Beams for heavy-ion fusion (HIF) are expected to require substantial neutralization in a target chamber. Present targets call for higher beam currents and smaller focal spots than most earlier designs, leading to high space-charge fields. Collisional stripping by the background gas expected in the chamber further increases the beam charge. Simulations with no electron sources other than beam stripping and background-gas ionization show an acceptable focal spot only for high ion energies or for currents far below the values assumed in recent HIF power-plant scenarios. Much recent research has, therefore, focused on beam neutralization by electron sources that were neglected in earlier simulations, including emission from walls and the target, photoionization by radiation from the target, and pre-neutralization by a plasma generated along the beam path. The simulations summarized here indicate that these effects can significantly reduce the beam focal-spot size.

Beams for heavy-ion fusion (HIF) are expected to require substantial neutralization in a target chamber. Present targets call for higher beam currents and smaller focal spots than most earlier designs, leading to high space-charge fields. Collisional stripping by the background gas expected in the chamber further increases the beam charge. Simulations with no electron sources other than beam stripping and background-gas ionization show an acceptable focal spot only for high ion energies or for currents far below the values assumed in recent HIF power-plant scenarios. Much recent research has, therefore, focused on beam neutralization by electron sources that were neglected in earlier simulations, including emission from walls and the target, photoionization by radiation from the target, and pre-neutralization by a plasma generated along the beam path. The simulations summarized here indicate that these effects can significantly reduce the beam focal-spot size.

Balloon-borne instruments detecting radiation belt precipitation frequently observe oscillations in the millihertz frequency range. Balloons measuring electron precipitation near the poles in the 100 keV to 2.5 MeV energy range, including the MAXIS, MINIS, and most recently the Balloon Array for Relativistic Radiation belt Electron Losses balloon experiments, have observed this modulation at ULF wave frequencies. Although ULF waves in the magnetosphere are seldom directly linked to increases in electron precipitation since their oscillation periods are much larger than the gyroperiod and the bounce period of radiation belt electrons, test particle simulations show that this interaction is possible. Three-dimensional simulations of radiation belt electrons were performed to investigate the effect of ULF waves on precipitation. The simulations track the behavior of energetic electrons near the loss cone, using guiding center techniques, coupled with an MHD simulation of the magnetosphere, using the Lyon-Fedder-Mobarry code, during a coronal mass ejection (CME)-shock event on 17 March 2013. Results indicate that ULF modulation of precipitation occurs even without the presence of electromagnetic ion cyclotron waves, which are not resolved in the MHD simulation. The arrival of a strong CME-shock, such as the one simulated, disrupts the electric and magnetic fields in the magnetosphere and causes significant changes in both components of momentum, pitch angle, and L shell of radiation belt electrons, which may cause them to precipitate into the loss cone.

Mountainous regions account for a significant part of the Earth's surface. Such areas are persistently affected by heavyprecipitation episodes, which induce flash floods and landslides. The limitation of inadequate in-situ observations has put remote sensing rainfall estimates on a pedestal concerning the analyses of these events, as in many mountainous regions worldwide they serve as the only available data source. However, well-known issues of remote sensing techniques over mountainous areas, such as the strong underestimation of precipitation associated with low-level orographic enhancement, limit the way these estimates can accommodate operational needs. Even locations that fall within the range of weather radars suffer from strong biases in precipitation estimates due to terrain blockage and vertical rainfall profile issues. A novel approach towards the reduction of error in quantitative precipitation estimates lies upon the utilization of high-resolution numerical simulations in order to derive error correction functions for corresponding satellite precipitation data. The correction functions examined consist of 1) mean field bias adjustment and 2) pdf matching, two procedures that are simple and have been widely used in gauge-based adjustment techniques. For the needs of this study, more than 15 selected storms over the mountainous Upper Adige region of Northern Italy were simulated at 1-km resolution from a state-of-the-art atmospheric model (RAMS/ICLAMS), benefiting from the explicit cloud microphysical scheme, prognostic treatment of natural pollutants such as dust and sea-salt and the detailed SRTM90 topography that are implemented in the model. The proposed error correction approach is applied on three quasi-global and widely used satellite precipitation datasets (CMORPH, TRMM 3B42 V7 and PERSIANN) and the evaluation of the error model is based on independent in situ precipitation measurements from a dense rain gauge network (1 gauge / 70 km2

Titanium and its alloys are used as biomaterials, because of their high biocompatibility. Apatite precipitates on a titania surface in vivo, and living bone and titanium alloy are coupled through the thin apatite layer. The initial precipitation behavior of apatite on titania in simulated body fluid (SBF) solutions was evaluated and the effect of inorganic ions in the SBF was investigated. Measurement using the SPR phenomenon was used to evaluate the initial apatite precipitation. An SBF containing approximately equal ion concentrations to those in blood plasma was added to a titania surface and the SPR profile was obtained, from which the initial apatite precipitation rate was found to be 1.14 nm/h. Furthermore, the relationship between the inorganic concentration and the precipitation rate was determined for SBFs with different Na+ and Ca2+ concentrations. Apatite precipitation did not occur in the SBF with a low Na+ concentration, whereas the initial apatite precipitation rate in the SBF that did not contain Ca2+ was 0.32 nm/h. According to these results, Ca2+ has little effect on the initial apatite precipitation. In the initial reaction of apatite precipitation, sodium titanate is formed by the absorption of Na+. Next, calcium titanate precipitates upon the substitution of Na+ with Ca2+. Finally, Na+, phosphate ions and hydroxyl ions are attracted to the surface and apatite is formed. Thus, the rate-limiting factor in the initial nucleation of apatite is the Na+ concentration.

Numerous studies have emphasized that climate simulations are subject to various biases and uncertainties. The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies and biases for both entire data distributions and their upper tails. The results of the Volumetric Hit Index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas, but that their replication of observed precipitation over arid regions and certain sub-continental regions (e.g., northern Eurasia, eastern Russia, central Australia) is problematical. Overall, the VHI of the multi-model ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (e.g., the 75th and 90th percentiles), all climate models display low skill in simulatingprecipitation, except over North America, the Amazon, and central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g. western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, inter-model variations in bias over Australia and Amazonia are considerable. The Quantile Bias (QB) analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. Lastly, we found that a simple mean-field bias removal improves the overall B and VHI values, but does not make a significant improvement in these model performance metrics at high quantiles of precipitation.

Neutrino-driven winds, which follow core-collapse supernova explosions, present a fascinating nuclear-astrophysics problem that requires an understanding of advanced astrophysics simulations, the properties of matter and neutrino interactions under extreme conditions, the structure and reactions of exotic nuclei, and comparisons with forefront astronomical observations. The neutrino-driven wind has attracted vast attention over the last 20 years as it was suggested as a candidate for the astrophysics site where half of the heavy elements are produced via the r-process. In this review, we summarize our present understanding of neutrino-driven winds from the dynamical and nucleosynthesis perspectives. Rapid progress has been made during recent years in understanding the wind with improved simulations and better micro physics. The current status of the fields is that hydrodynamical simulations do not reach the extreme conditions necessary for the r-process, and the proton or neutron richness of the wind remains to be investigated in more detail. However, nucleosynthesis studies and observations already point to neutrino-driven winds to explain the origin of lighter heavy elements, such as Sr, Y, Zr.

The objective of this study is to cross-validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies, and biases for both entire distributions and their upper tails. The results of the volumetric hit index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas but that their replication of observed precipitation over arid regions and certain subcontinental regions (e.g., northern Eurasia, eastern Russia, and central Australia) is problematical. Overall, the VHI of the multimodel ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (75th and 90th percentiles), all climate models display low skill in simulatingprecipitation, except over North America, the Amazon, and Central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g., western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, intermodel variations in bias over Australia and Amazonia are considerable. The quantile bias analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. It is found that a simple mean field bias removal improves the overall B and VHI values but does not make a significant improvement at high quantiles of precipitation.

A simple statistical downscaling procedure for transforming daily global climate model (GCM) rainfall was applied at the local scale in Katumani, Kenya. We corrected the rainfall frequency bias of the GCM by truncating its daily rainfall cumulative distribution into the station's distribution using a wet-day threshold. Then, we corrected the GCM's rainfall intensity bias by mapping its truncated rainfall distribution into the station's truncated distribution. Additional tailoring was made to the bias corrected GCM rainfall by linking it with a stochastic disaggregation scheme based on a conditional stochastic weather generator to correct the temporal structure inherent with daily GCM rainfall. Results of the simple and hybridized GCM downscaled precipitation variables (total, probability of occurrence, intensity and dry spell length) were linked with a crop model. An objective evaluation of the tailored GCM data was done using entropy. This study is useful for the identification of the most suitable downscaling technique, as well as the most effective precipitation variables for forecasting crop yields.

In recent decades, Southern Hemisphere midlatitude regions such as southern Africa, southeastern Australia and southern Chile have experienced a reduction in austral autumn precipitation; the cause of which is poorly understood. This study focuses on the ability of climate models that form part of the Coupled Model Intercomparison Project phase 5 to simulate these trends, their relationship with extratropical and subtropical processes, and implications for future precipitation changes. Models underestimate both the historical autumn poleward expansion of the subtropical dry zone and the positive Southern Annular Mode (SAM) trend. The multi-model ensemble (MME) is also unable to capture the spatial pattern of observed precipitation trends across semi-arid midlatitude regions. However, in temperate regions that are located further poleward such as southern Chile, the MME simulates observed precipitation declines. The MME shows a strong consensus in twenty-first century declines in autumn precipitation across southern Chile in both the medium-low and high Representative Concentration Pathway (RCP) scenarios, and across southern Africa in the high RCP scenario, but little change across southeastern Australia. Projecting a strong positive SAM trend and continued subtropical dry-zone expansion, the models converge on large SAM and dry-zone expansion-induced precipitation declines across southern midlatitudes. In these regions, the strength of future precipitation trends is proportional to the strength of modelled trends in these phenomena, suggesting that unabated greenhouse gas-induced climate change will have a large impact on austral autumn precipitation in such midlatitude regions.

At present the investigation of the chemical composition of precipitation is a very actual task in the monitoring of environmental pollution. It is known that heavy metals can be the indices of the anthropogenic atmospheric pollution. The emissions from the mining enterprises, of non-ferrous metallurgy, of chemical industry, from heat-and-power production plants, from transport vehicles fare the sources of the heavy metals ingress into the atmosphere. Their emissions in atmosphere form fine-disperse aerosol fractions and afterwards they fall down together with precipitation onto the underlying surface. Heavy metals have the property of accumulation in environmental objects, which disturbs its ecological balance. One of the problems of the study of the influence of heavy metals pollution on the environment is their travel with the air masses of different origin on large distance. In this concern it is interesting to study the content of the heavy metals in atmospheric aerosols and precipitation in the background zones. Chatkal nature reservation on the territory of Tashkent province presents such background point. For the estimation of the level of atmospheric pollution by heavy metals and evaluation of the possible impact on the background level of air pollution of Chatkal nature reservation by anthropogenic sources (industrial cities of the capital province of Uzbekistan) the data analysis was carried out by the Administration of Environment Pollution Monitoring (AEPM) of hydrometeorological service of the Republic of Uzbekistan. It is necessary to mention that Chatkal biospheric nature reservation is situated in 100 km from Tashkent (the capital of the Republic of Uzbekistan) and in 60 km from Almalyk (the biggest centre of mining-metallurgical and chemical industry of the republic). The station of the complex background monitoring of atmospheric pollution (SCBM) is situated on the territory of this nature reservation. This area is characterized by a typical

The Plant-Craig (PC) stochastic convective parameterization scheme is implemented into the National Center for Atmospheric Research Community Atmosphere Model version 5 (CAM5) to couple with the Zhang-McFarlane deterministic convection scheme. To evaluate its impact on tropical precipitationsimulation, two experiments are conducted: one with the standard CAM5 and the other with the stochastic scheme incorporated. Results show that the PC stochastic parameterization decreases the frequency of weak precipitation and increases the frequency of strong precipitation, resulting in better agreement with observations. The most striking improvement is in the probability distribution function (PDF) of precipitation intensity, with the well-known too-much-drizzle problem in CAM5 largely eliminated. In the global tropical belt, the precipitation intensity PDF from the simulation agrees remarkably well with that of Tropical Rainfall Measuring Mission observations. The stochastic scheme also yields a similar magnitude of intraseasonal variability of precipitation to observations and improves the simulation of the eastward propagating intraseasonal signals of precipitation and zonal wind.

The Mediterranean region is frequently affected by heavyprecipitation events associated with flash-floods, landslides and mudslides each year that cost several billions of dollars in damage and causing too often casualties. Within the framework of the 10-year international HyMeX program dedicated to the hydrological cycle and related processes in the Mediterranean (http://www.hymex.org), a major field campaign has been dedicated to heavyprecipitation and flash-floods from September to November 2012. The 2-month field campaign took place over the Northwestern Mediterranean Sea and its surrounding coastal regions in France, Italy and Spain. The observation strategy aimed at documenting four key components leading to heavyprecipitation and flash-flooding in that region: (i) the marine atmospheric flow that transport moist and conditionaly unstable air towards the coasts; (ii) the Mediterranean Sea as a moisture and energy source; (iii) the dynamics and microphysics of the convective systems; (iv) the hydrological processes during flash-floods. During the field campaign about twenty precipitation events were monitored, including mesoscale convective systems, Mediterranean cyclogenesis, shallow-convection orographic precipitation. Three aircraft performed about 250 flight hours for a survey of the upstream flow, the air-sea fluxes and the convective systems. About 700 additional radiosoundings were launched either from HyMeX sites or from operational RS sites in Europe, as well as about 20 boundary layer balloons were launched to monitor the low-level flow over the Mediterranean Sea and the ambient atmospheric conditions. Gliders, Argo floats, drifting buoys and ocean soundings from vessels monitored the Mediterranean Sea during the field campaign. Atmospheric and hydrological instruments such as radars, LIDARS, radiometers, wind profilers, lightning sensors, were deployed over 5 regions in France, Italy and Spain. The presentation will present the general

The Weather Research and Forecast (WRF-ARW) model, version 3.3.1, was used to perform the European domain Cordex simulations, at 50km resolution. A first simulation, forced by ERA-Interim (1989-2009), was carried out to evaluate the models performance to represent the mean and extreme precipitation in present European climate. This evaluation is based in the comparison of WRF results against the ECAD regular gridded dataset of daily precipitation. Results are comparable to recent studies with other models for the European region, at this resolution. For the same domain a control and a future scenario (RCP8.5) simulation was performed to assess the climate change impact on the mean and extreme precipitation. These regional simulations were forced by EC-EARTH model results, and, encompass the periods from 1960-2006 and 2006-2100, respectively.

Contaminating clouds of electrons are a concern for most accelerators of positive-charged particles, but there are some unique aspects of heavy-ion accelerators for fusion and high-energy density physics which make modeling such clouds especially challenging. In particular, self-consistent electron and ion simulation is required, including a particle advance scheme which can follow electrons in regions where electrons are strongly-, weakly-, and un-magnetized. They describe their approach to such self-consistency, and in particular a scheme for interpolating between full-orbit (Boris) and drift-kinetic particle pushes that enables electron time steps long compared to the typical gyro period in the magnets. They present tests and applications: simulation of electron clouds produced by three different kinds of sources indicates the sensitivity of the cloud shape to the nature of the source; first-of-a-kind self-consistent simulation of electron-cloud experiments on the High-Current Experiment (HCX) at Lawrence Berkeley National Laboratory, in which the machine can be flooded with electrons released by impact of the ion beam and an end plate, demonstrate the ability to reproduce key features of the ion-beam phase space; and simulation of a two-stream instability of thin beams in a magnetic field demonstrates the ability of the large-timestep mover to accurately calculate the instability.

Computer simulations of intense ion beams play a key role in the Heavy Ion Fusion research program. Along with analytic theory, they are used to develop future experiments, guide ongoing experiments, and aid in the analysis and interpretation of experimental results. They also afford access to regimes not yet accessible in the experimental program. The U.S. Heavy Ion Fusion Virtual National Laboratory and its collaborators have developed state-of-the art computational tools, related both to codes used for stationary plasmas and to codes used for traditional accelerator applications, but necessarily differing from each in important respects. These tools model beams in varying levels of detail and at widely varying computational cost. They include moment models (envelope equations and fluid descriptions), particle-in-cell methods (electrostatic and electromagnetic), nonlinear-perturbative descriptions (''{delta}f''), and continuum Vlasov methods. Increasingly, it is becoming clear that it is necessary to simulate not just the beams themselves, but also the environment in which they exist, be it an intentionally-created plasma or an unwanted cloud of electrons and gas. In this paper, examples of the application of simulation tools to intense ion beam physics are presented, including support of present-day experiments, fundamental beam physics studies, and the development of future experiments. Throughout, new computational models are described and their utility explained. These include Mesh Refinement (and its dynamic variant, Adaptive Mesh Refinement); improved electron cloud and gas models, and an electron advance scheme that allows use of larger time steps; and moving-mesh and adaptive-mesh Vlasov methods.

Kiremt-season (June-September) precipitation provides a significant water supply for Ethiopia, particularly in the central and northern regions. The response of Kiremt-season precipitation to climate change is thus of great concern to water resource managers. However, the complex processes that control Kiremt-season precipitation challenge the capability of general circulation models (GCMs) to accurately simulateprecipitation amount and variability. This in turn raises questions about their utility for predicting future changes. This study assesses the impact of climate change on Kiremt-season precipitation using state-of-the-art GCMs participating in the Coupled Model Intercomparison Project Phase 5. Compared to models with a coarse resolution, high-resolution models (horizontal resolution <2°) can more accurately simulateprecipitation, most likely due to their ability to capture precipitation induced by topography. Under the Representative Concentration Pathway (RCP) 4.5 scenario, these high-resolution models project an increase in precipitation over central Highlands and northern Great Rift Valley in Ethiopia, but a decrease in precipitation over the southern part of the country. Such a dipole pattern is attributable to the intensification of the North Atlantic subtropical high (NASH) in a warmer climate, which influences Ethiopian Kiremt-season precipitation mainly by modulating atmospheric vertical motion. Diagnosis of the omega equation demonstrates that an intensified NASH increases (decreases) the advection of warm air and positive vorticity into the central Highlands and northern Great Rift Valley (southern part of the country), enhancing upward motion over the northern Rift Valley but decreasing elsewhere. Under the RCP 4.5 scenario, the high-resolution models project an intensification of the NASH by 15 (3 × 105 m2 s-2) geopotential meters (stream function) at the 850-hPa level, contributing to the projected precipitation change over Ethiopia. The

We analyze the ability of global and regional climate models to simulate extreme daily precipitation and supporting processes for midlatitude and Arctic regions of North America. Regional model output comes from the NARCCAP archive and simulations by an Arctic version of WRF; global model output comes from the CMIP5 archive. The NARCCAP results also include output from a time-slice, high-resolution global simulation. All regional model output is at half degree resolution, whereas the CMIP5 resolutions vary but are coarser than the regional model resolutions. The combined analysis allows us to assess added value of finer resolution in simulating extreme precipitation. Analysis focuses on selected regions of North America for winter (DJF) and summer (JJA), building on several previous analyses focused on this region. In addition to comparing results from the different models, we also compare simulatedprecipitation and supporting processes with those obtained from observed precipitation and reanalysis atmospheric states. In the central U.S., the models generally reproduce well the precipitation-vs.-intensity spectrum seen in observations, with a tendency for coarse-resolution global models to produce somewhat less intense precipitation. In contrast, all models are deficient in high intensity precipitation in Alaska. Further analysis focuses on precipitation events exceeding the 99.5 percentile that occur simultaneously at several points in the region, yielding so-called "widespread events". Analysis of 500 hPa heights, near-surface circulation and fields such as temperature and humidity reveal the processes leading to extreme events in the models and observations. The finer resolution models generally reproduce the physical behavior of these extreme events, with the coarser models showing a smoother rendition. In the central U.S., for winter, these events are produced by slowly moving low-pressure systems that all models simulate fairly well. In Alaska, these events

Land use/land cover (LU/LC) changes are considered to be one of the most important factors affecting regional climate and are thus an area of public concern. The land surface plays a crucial role in boundary layer evolution and precipitation patterns thereby establishing the need for LU/LC inputs as a critical part of modeling systems. Inaccurate LU/LC information often leads to very large errors in surface energy fluxes thus leading to errors in boundary layer state. We have investigated an incident of heavy rainfall during August 2015 over West Bengal, India using Weather Research and Forecast (WRF) model by incorporating different LU/LC datasets, IRS P6 Advanced Wide Field Sensor (AWiFS) LU/LC data for 2012-13 and the default Moderate Resolution Imaging Spectro-radiometer (MODIS) derived USGS LU/LC data for 2001. In the present study, we have made a comparative assessment between AWiFS derived LU/LC and USGS LU/LC by incorporating these datasets as one of the lower boundary conditions over Indian region in WRF model version 3.5.1 to simulate, at 10km resolution, a heavy rainfall event associated with landfall of a cyclonic system over West Bengal. The results of the study suggested influence of LU/LC in occurrence of heavy rainfall with WRF model using AWiFS LU/LC showing more realistic simulation as AWiFS LU/LC is more up-to-date and features recent changes in LU/LC over India.

General circulation model (GCM) simulations of atmospheric circulation are more reliable than GCM simulations of temperature and precipitation. In this study, temporal correlations between 700 hPa height anomalies simulated winter precipitation at eight locations in the conterminous United States are compared with corresponding correlations in observations. The objectives are to 1) characterize the relations between atmospheric circulation and winter precipitationsimulated by the GFDL, GCM for selected locations in the conterminous USA, ii) determine whether these relations are similar to those found in observations of the actual climate system, and iii) determine if GFDL-simulatedprecipitation is forced by the same circulation patterns as in the real atmosphere. -from Authors

In this study, the regional climate model of RegCM3 is applied to investigate the sensitivity of regional climate over China using four cumulus parameterizations, the modified Anthes-Kuo (AK), the Grell with Arakawa-Schubert closure, the Grell with Fritsch-Chappell closure, and the MIT-Emanuel (EM). The model was integrated over the period of 1982 to 2001 using the NCEP Reanalysis data NNRP2 as boundary conditions. RegCM3 coupled with various cumulus parameterizations is evaluated firstly as for its ability to represent regional climatology and climate extreme indices, and the results show that simulated regional climate in China is sensitive to the option of cumulus parameterizations. All the cumulus schemes produce a northward expansion of heavy rain area and an underestimation of surface air temperature. For precipitation, the AK scheme simulates relatively better magnitude, while the EM scheme has more reliable performance on the spatial distribution. RegCM3 can represent the spatial distributions of extreme indices for both precipitation and temperature, as well as their decadal trends irrelevant to the cumulus parameterizations. However, the model underestimates the consecutive dry days and overestimates the three extreme wet indices, with the EM scheme giving the worst result. Slight underestimations of extreme temperature indices are detected in all cumulus parameterization scheme runs. The shapes of probability distribution functions for extreme indices are correctly produced, though the probabilities of extreme dry and warm events are underestimated.

The study evaluates relationships between large-scale atmospheric circulation (represented by circulation indices and circulation types derived from gridded mean sea level pressure) and daily precipitation amounts over three regions in the Czech Republic (Central Europe) with different precipitation regimes. We examine how ENSEMBLES regional climate model (RCM) simulations driven by re-analysis reproduce the observed links and capture differences in the links between the regions (lowlands vs. highlands) and seasons. We study the links of circulation to (i) mean precipitation over the regions, (ii) probability of wet days, and (iii) probability of extreme daily precipitation (exceeding threshold defined by a high quantile of precipitation distribution in a given season). Relatively strong links between atmospheric circulation and the precipitation characteristics are found in the observed data. The links are generally more pronounced for highland than lowland regions. More wet days and higher precipitation amounts are found for cyclonic and stronger flows, and for westerly and north-easterly flows. The RCMs are generally able to capture basic features of the links; nevertheless, they have difficulties to reproduce some more specific features and differences in the links between the regions. The results also suggest that good performance in some precipitation characteristics may be due to compensating errors rather than model's perfection. Reference: Plavcová E., Kyselý J., Štěpánek P., 2014: Links between circulation types and precipitation in Central Europe in the observed data and regional climate model simulations. International Journal of Climatology, doi 10.1002/joc.3882.

One of the seven scientific areas of interests of the 7-SEAS field campaign is to evaluate the impact of aerosol on cloud and precipitation (http://7-seas.gsfc.nasa.gov). However, large-scale covariability between aerosol, cloud and precipitation is complicated not only by ambient environment and a variety of aerosol effects, but also by effects from rain washout and climate factors. This study characterizes large-scale aerosol-cloud-precipitation covariability through synergy of long-term multi ]sensor satellite observations with model simulations over the 7-SEAS region [10S-30N, 95E-130E]. Results show that climate factors such as ENSO significantly modulate aerosol and precipitation over the region simultaneously. After removal of climate factor effects, aerosol and precipitation are significantly anti-correlated over the southern part of the region, where high aerosols loading is associated with overall reduced total precipitation with intensified rain rates and decreased rain frequency, decreased tropospheric latent heating, suppressed cloud top height and increased outgoing longwave radiation, enhanced clear-sky shortwave TOA flux but reduced all-sky shortwave TOA flux in deep convective regimes; but such covariability becomes less notable over the northern counterpart of the region where low ]level stratus are found. Using CO as a proxy of biomass burning aerosols to minimize the washout effect, large-scale covariability between CO and precipitation was also investigated and similar large-scale covariability observed. Model simulations with NCAR CAM5 were found to show similar effects to observations in the spatio-temporal patterns. Results from both observations and simulations are valuable for improving our understanding of this region's meteorological system and the roles of aerosol within it. Key words: aerosol; precipitation; large-scale covariability; aerosol effects; washout; climate factors; 7- SEAS; CO; CAM5

In recent years, because the frequency and severity of floods have increased across Canada, it is important to understand the characteristics of Canadian heavyprecipitation. Long-term precipitation data of 463 gauging stations of Canada were analyzed using non-stationary generalized extreme value distribution (GEV), Poisson distribution and generalized Pareto (GP) distribution. Time-varying covariates that represent large-scale climate patterns such as El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific decadal oscillation (PDO) and North Pacific Oscillation (NP) were incorporated to parameters of GEV, Poisson and GP distributions. Results show that GEV distributions tend to under-estimate annual maximum daily precipitation (AMP) of western and eastern coastal regions of Canada, compared to GP distributions. Poisson regressions show that temporal clusters of heavyprecipitation events in Canada are related to large-scale climate patterns. By modeling AMP time series with non-stationary GEV and heavyprecipitation with non-stationary GP distributions, it is evident that AMP and heavyprecipitation of Canada show strong non-stationarities (abrupt and slowly varying changes) likely because of the influence of large-scale climate patterns. AMP in southwestern coastal regions, southern Canadian Prairies and the Great Lakes tend to be higher in El Niño than in La Niña years, while AMP of other regions of Canada tends to be lower in El Niño than in La Niña years. The influence of ENSO on heavyprecipitation was spatially consistent but stronger than on AMP. The effect of PDO, NAO and NP on extreme precipitation is also statistically significant at some stations across Canada.

The Materials Process Modeling Division, IMR, CAS has been promoting for more than 10 years research activities on modeling and experimental studies on heavy castings and forgings. In this report, we highlight some selected achievements and impacts in this area: To satisfy domestic strategic requirements, such as nuclear and hydraulic power, marine projects and high speed rail, we have developed a number of casting and forging technologies, which combine advanced computing simulations, X-ray real time observation techniques and industrial-scaled trial experiments. These technologies have been successfully applied in various industrial areas and yielded a series of scientific and technological breakthroughs and innovation. Important examples of this strategic research include the hot-processing technologies of the Three Gorge water turbine runner, marine crankshaft manufacturers, backup rolls for hot rolling mills and the production of hundreds-ton steel ingot.

An automated separation technique was developed that provides a new approach to measuring the distribution profiles of the most polar, or asphaltenic components of an oil, using a continuous flow system to precipitate and re-dissolve asphaltenes from the oil. Methods of analysis based on this new technique were explored. One method based on the new technique involves precipitation of a portion of residua sample in heptane on a polytetrafluoroethylene-packed (PTFE) column. The precipitated material is re-dissolved in three steps using solvents of increasing polarity: cyclohexane, toluene, and methylene chloride. The amount of asphaltenes that dissolve in cyclohexane is a useful diagnostic of the thermal history of oil, and its proximity to coke formation. For example, about 40 % (w/w) of the heptane asphaltenes from unpyrolyzed residua dissolves in cyclohexane. As pyrolysis progresses, this number decrease to below 15% as coke and toluene insoluble pre-coke materials appear. Currently, the procedure for the isolation of heptane asphaltenes and the determination of the amount of asphaltenes soluble in cyclohexane spans three days. The automated procedure takes one hour. Another method uses a single solvent, methylene chloride, to re-dissolve the material that precipitates on heptane on the PTFE-packed column. The area of this second peak can be used to calculate a value which correlates with gravimetric asphaltene content. Currently the gravimetric procedure to determine asphaltenes takes about 24 hours. The automated procedure takes 30 minutes. Results for four series of original and pyrolyzed residua were compared with data from the gravimetric methods. Methods based on the new on-column precipitation and re-dissolution technique provide significantly more detail about the polar constituent's oils than the gravimetric determination of asphaltenes.

Mercury (II) (Hg(2+)) ion can be reduced by aqueous S(IV) (sulfite and/or bisulfite) species, which leads to elemental mercury (Hg(0)) emissions in wet flue gas desulfurization (FGD) systems. Numerous reports have demonstrated the high trapping efficiency of sodium dithiocarbamate over heavy metals. In this paper, a novel sodium dithiocarbamate, DTCR, was utilized as a precipitator to control Hg(2+) reduction and Hg(0) emission against S(IV) in FGD solutions. Results indicated that Hg(2+) reduction efficiency decreased dramatically while precipitation rate peaked at around 91.0% in consistence with the increment of DTCR dosage. Initial pH and temperature had great inhibitory effects on Hg(2+) reduction: the Hg(2+) removal rate gradually increased and reached a plateau along with the increment of temperature and initial pH value. Chloride played a key role in Hg(2+) reduction and precipitation reactions. When Cl(-) concentration increased from 0 to 150 mM, Hg(2+) removal rate dropped from 93.84% to 86.05%, and the Hg(2+) reduction rate remained at a low level (<7.8%). SO(4)(2-), NO(3)(-) and other common metal ions would affect the efficiency of Hg(2+) reduction and precipitation reactions in the simulated desulfurization solutions: Hg(2+) removal rate could always be above 90%, while Hg(2+) reduction rate was maintained at below 10%. The predominance of DTCR over aqueous S(IV), indicated by the results above, has wide industrial applications in FGD systems. PMID:21955657

Projected changes in precipitation characteristics around the mid-21st century and end-of-the-century are analyzed using the daily precipitation output of the 3-member ensemble Meteorological Research Institute global ocean-atmosphere coupled general circulation model (MRI-CGCM2) simulations under the Special Report on Emissions Scenarios (SRES) A2 and B2 scenarios. It is found that both the frequency and intensity increase in about 40% of the globe, while both the frequency and intensity decrease in about 20% of the globe. These numbers differ only a few percent from decade to decade of the 21st century and between the A2 and B2 scenarios. Over the rest of the globe (about one third), the precipitation frequency decreases but its intensity increases, suggesting a shift of precipitation distribution toward more intense events by global warming. South China is such a region where the summertime wet-day frequency decreases but the precipitation intensity increases. This is related to increased atmospheric moisture content due to global warming and an intensified and more westwardly extended North Pacific subtropical anticyclone, which may be related with an El Niño-like mean sea surface temperature change. On the other hand, a decrease in summer precipitation is noted in North China, thus augmenting a south-to-north precipitation contrast more in the future.

The objective of the present paper is to examine the capability of the regional climate model version 3 (RegCM3) to simulate the annual as well as seasonal precipitation variability over the Indian subcontinent. RegCM3 has been run at 40 km horizontal resolution for the period of 1982-2006 continuously and model results were compared to the observed precipitation datasets of India Meteorological Department (IMD) and CPC Merged Analysis of Precipitation (CMAP). Model evaluation has been done using different statistical methods like mean bias error (MBE), root mean square error, mean percentage error (MPE) and studied the spatial pattern of annual and seasonal variability and trend. Daily precipitation data at 1° × 1° grids of IMD have been used to study observed climatological means (both annual and seasonal), regression trends, interannual and intraseasonal variability over India from 1951 to 2007. The spatial distribution of annual precipitation shows a decreasing trend over west coast of India, central India, hilly region of India and an increasing trend is found over the northwest India, peninsular India and northeast India. The temporal distribution of daily precipitation shows highest rainfall of 18 mm/day in mid July (in composite flood cases only) and 12 mm/day during August (in composite drought cases only). The RegCM3 simulated annual and seasonal precipitation variability is close to the observed IMD and CMAP over all India (AI). During winter and pre-monsoon season, the model has overestimated the mean precipitation while underestimated in summer and post-monsoon season. Overall, annual precipitation showed the deficiency of -22.44 % compared to IMD and -1.41 % compared to CMAP over India. To understand the possible cause of annual and seasonal precipitation biases over India and its six homogeneous regions, the vertical difference (model mines National Centre for Environmental Prediction; NCEP) fields of water vapor mixing ratio (WVMR) and air

Balloon-borne instruments detecting radiation belt precipitation frequently observe oscillations in the mHZ frequency range. Several balloon missions measuring electron precipitation near the poles in the 100 keV to 2.5 MeV energy range, including the MAXIS, MINIS, and most recently the BARREL campaign, have observed this modulation at ULF wave frequencies (Clilverd et al., 2007; Millan et al., 2011). However, ULF waves in the magnetosphere, commonly associated with oscillations in solar wind dynamic pressure on the dayside and with Kelvin-Helmhotz instabilities in the flanks, are seldom directly linked to increases in electron precipitation since their oscillation periods are much larger than the gyroperiod and the bounce period of radiation belt electrons. It has been conjectured that ULF oscillations in the magnetosphere may modulate EMIC wave growth rates. EMIC waves, in turn, have long been associated with energetic electron precipitation, since they can cause pitch angle scattering of these particles, thus lowering their mirror points (Miyoshi et al., 2008; Carson et al., 2013). This would explain the ULF modulation of MeV electrons seen by the balloon instruments. However, test particle simulations show that another hypothesis is possible (Brito et al., 2012). 3D simulations of radiation belt electrons were performed to investigate the effect of ULF waves on precipitation. The simulations track the behavior of energetic electrons near the loss cone, using guiding center techniques, coupled with an MHD simulation of the magnetosphere, using the LFM code, during a CME-shock event on March 17, 2013. Results indicate that ULF modulation of precipitation occurs even without the presence of VLF-type waves, which are not resolved in the MHD simulation.

In Acid Mine Drainage (AMD) settings colloidal precipitates control the mobility of Potential Toxic Elements (PTEs). Mineral-contaminant relationships (i.e. adsorption, ion-exchange, desorption) are rarely pure abiotic processes. Microbes, mainly bacteria and microfungi, can catalyze several reactions modifying the element speciation, as well as the bioavailability of inorganic pollutants. Soil, sediments, and waters heavily polluted with PTEs through AMD processes are a potential reservoir of extremophile bacteria and fungi exploitable for biotechnological purposes. Two different AMD related colloids, an ochraceous precipitate (deposited in weakly acidic conditions, composed by nanocrystalline goethite) and a greenish-blue precipitate (deposited at near-neutral pH, composed by allophane + woodwardite) were sampled. The aims of this work were to a) characterize the mycobiota present in these colloidal minerals by evaluating the presence of alive fungal propagules and extracting bacteria DNA; b) verify the fungal strains tolerance, and bioaccumulation capability on greenish-blue and ZnSO4 enriched media; c) evaluate potential impact of bacteria in the system geochemistry. The preliminary results show an interesting and selected mycobiota able to survive under unfavourable environmental conditions. A significant number of fungal strains were isolated in pure culture. Among them, species belonging to Penicillium and Trichoderma genera were tested on both greenish-blue and ZnSO4 enriched media. The results show a significant tolerance and bioaccumulation capability to some PTEs. The same colloidal precipitates were processed to extract bacteria DNA by using a specific procedure developed for sediments. The results give a good yield of nucleic acids and a positive PCR amplification of 16S rDNA accomplished the first step for future metagenomic analyses.

Istanbul Technical University, Aeronautics and Astronautics Faculty, Meteorological Engineering, Istanbul, Turkey In this study, we examined the extreme precipitation case over the Eastern Black Sea region of Turkey by using regional climate model, RegCM4. The flood caused by excessive rain in August 26, 2010 killed 12 people and the landslides in Rize province have damaged many buildings. The station based two days total precipitation exceeds 200 mm. One of the usual suspects for this extreme event is positive anomaly of sea surface temperature (SST) over the Black Sea where the significant warming trend is clear in the last three decades. In August 2010, the monthly mean SST is higher than 3 °C with respect to the period of 1981-2010. We designed three sensitivity simulations with RegCM4 to define the effects of the Black Sea as a moisture source. The simulation domain with 10-km horizontal resolution covers all the countries bordering the Black Sea and simulation period is defined for entire August 2010. It is also noted that the spatial variability of the precipitation produced by the reference simulation (Sim-0) is consistent with the TRMM data. In terms of analysis of the sensitivity to SST, we forced the simulations by subtracting 1 °C (Sim-1), 2 °C (Sim-2) and 3 °C (Sim-3) from the ERA-Interim 6-hourly SST data (considering only the Black Sea). The sensitivity simulations indicate that daily total precipitation for all these simulations gradually decreased based on the reference simulation (Sim-0). 3-hourly maximum precipitation rates for Sim-0, Sim-1, Sim-2 and Sim-3 are 32, 25, 13 and 10.5 mm respectively over the hotspot region. Despite the fact that the simulations signal points out the same direction, degradation of the precipitation intensity does not indicate the same magnitude for all simulations. It is revealed that 2 °C (Sim-2) threshold is critical for SST sensitivity. We also calculated the humidity differences from the simulation and these

To study the variations of deltaD and delta18O in precipitation, 301 samples were sampled during 2002-2004 in 6 sites in the Heihe River basin, Northwestern China. The deltaD and delta18O values ranged from 59 per thousand to -254 per thousand and 6.5 per thousand to -33.4 per thousand, respectively. This wide range indicated that stable isotopes in precipitation were controlled by different condensation mechanisms as a function of air temperature and varying sources of moisture. delta18O in precipitation had a close positive relationship with the air temperature, i. e., a clear temperature effect existed in this area. At a monthly scale, no precipitation effect existed. On the other hand, a weak precipitation effect still accrued at precipitation events scale. The spatial variation of delta18O showed that the weighted average delta18O values decreased with the increasing altitude of sampling sites at a gradient of -0. 47 per thousand/100m. A regional Meteoric Water Line, deltaD = 7.82 delta18O + 7.63, was nearly identical to the Meteoric Water Line in the Northern China. The results of backward trajectory of each precipitation day at Xishui showed that the moisture of the precipitation in cold season (October to March) mainly originated from the west while the moisture source was more complicated in warm season (April to September). The simulation of seasonal delta18O variation showed that the stable isotope composition of precipitation tended to a clear sine-wave seasonal variation. PMID:21922801

An ensemble of six pairs of RCM experiments performed at 25 and 50 km for the period 1961-2000 over a large European domain is examined in order to evaluate the effects of resolution on the simulation of daily precipitation statistics. Application of the non-parametric two-sample Kolmorgorov-Smirnov test, which tests for differences in the location and shape of the probability distributions of two samples, shows that the distribution of daily precipitation differs between the pairs of simulations over most land areas in both summer and winter, with the strongest signal over southern Europe. Two-dimensional histograms reveal that precipitation intensity increases with resolution over almost the entire domain in both winter and summer. In addition, the 25 km simulations have more dry days than the 50 km simulations. The increase in dry days with resolution is indicative of an improvement in model performance at higher resolution, while the more intense precipitation exceeds observed values. The systematic increase in precipitation extremes with resolution across all models suggests that this response is fundamental to model formulation. Simple theoretical arguments suggest that fluid continuity, combined with the emergent scaling properties of the horizontal wind field, results in an increase in resolved vertical transport as grid spacing decreases. This increase in resolution-dependent vertical mass flux then drives an intensification of convergence and resolvable-scale precipitation as grid spacing decreases. This theoretical result could help explain the increasingly, and often anomalously, large stratiform contribution to total rainfall observed with increasing resolution in many regional and global models.

In this study, we apply an efficient sampling approach and conduct a large number of simulations to explore the sensitivity of the simulated Asian summer monsoon (ASM) precipitation, including the climatological state and interannual variability, to eight parameters related to the cloud and precipitation processes in the Beijing Climate Center AGCM version 2.1 (BCC_AGCM2.1). Our results show that BCC_AGCM2.1 has large biases in simulating the ASM precipitation. The precipitation efficiency and evaporation coefficient for deep convection are the most sensitive parameters in simulating the ASM precipitation. With optimal parameter values, the simulatedprecipitation climatology could be remarkably improved, e.g. increased precipitation over the equator Indian Ocean, suppressed precipitation over the Philippine Sea, and more realistic Meiyu distribution over Eastern China. The ASM precipitation interannual variability is further analyzed, with a focus on the ENSO impacts. It shows the simulations with better ASM precipitation climatology can also produce more realistic precipitation anomalies during El Niño decaying summer. In the low-skill experiments for precipitation climatology, the ENSO-induced precipitation anomalies are most significant over continents (vs. over ocean in observation) in the South Asian monsoon region. More realistic results are derived from the higher-skill experiments with stronger anomalies over the Indian Ocean and weaker anomalies over India and the western Pacific, favoring more evident easterly anomalies forced by the tropical Indian Ocean warming and stronger Indian Ocean-western Pacific tele-connection as observed. Our model results reveal a strong connection between the simulated ASM precipitation climatological state and interannual variability in BCC_AGCM2.1 when key parameters are perturbed.

Plugging of flow paths caused by mineral precipitation in fractures above the potential repository at Yucca Mountain, Nevada could reduce the probability of water seeping into the repository. As part of an ongoing effort to evaluate thermal-hydrological-chemical (THC) effects on flow in fractured media, we performed a laboratory experiment and numerical simulations to investigate mineral dissolution and precipitation under anticipated temperature and pressure conditions in the repository. To replicate mineral dissolution by vapor condensate in fractured tuff, water was flowed through crushed Yucca Mountain tuff at 94 degrees C. The resulting steady-state fluid composition had a total dissolved solids content of about 140 mg/l; silica was the dominant dissolved constituent. A portion of the steady-state mineralized water was flowed into a vertically oriented planar fracture in a block of welded Topopah Spring Tuff that was maintained at 80 degrees C at the top and 130 degrees C at the bottom. The fracture began to seal with amorphous silica within 5 days.A 1-D plug-flow numerical model was used to simulate mineral dissolution, and a similar model was developed to simulate the flow of mineralized water through a planar fracture, where boiling conditions led to mineral precipitation. Predicted concentrations of the major dissolved constituents for the tuff dissolution were within a factor of 2 of the measured average steady-state compositions. The mineral precipitationsimulations predicted the precipitation of amorphous silica at the base of the boiling front, leading to a greater than 50-fold decrease in fracture permeability in 5 days, consistent with the laboratory experiment.These results help validate the use of a numerical model to simulate THC processes at Yucca Mountain. The experiment and simulations indicated that boiling and concomitant precipitation of amorphous silica could cause significant reductions in fracture porosity and permeability on a local

Geochemical modeling plays an increasingly vital role in a number of areas of geoscience, ranging from groundwater and surface water hydrology to environmental preservation and remediation. Geochemical modeling is also used to model the interaction processes at the water - sediment interface in acid mine drainage (AMD). AMD contains high concentrations of sulfate and dissolved metals and it is a serious environmental problem in eastern Slovakia. The paper is focused on comparing the results of laboratory precipitation of metal ions from AMD (the Smolnik creek, Slovakia) with the results obtained by geochemical modeling software Visual Minteq 3.0.

Highly alkaline nuclear waste solutions have been released from underground nuclear waste storage tanks and pipelines into the vadose zone at the U.S. Department of Energy’s Hanford Site in Washington, causing mineral dissolution and re-precipitation upon contact with subsurface sediments. High pH caustic NaNO3 solutions with and without dissolved Al were reacted with quartz sand through flow-through columns stepwise at 45, 51, and 89°C to simulate possible reactions between leaked nuclear waste solution and primary subsurface mineral. Upon reaction, Si was released from the dissolution of quartz sand, and nitrate-cancrinite [Na8Si6Al6O24(NO3)2] precipitated on the quartz surface as a secondary mineral phase. Both steady-state dissolution and precipitation kinetics were quantified, and quartz dissolution apparent activation energy was determined. Mineral alteration through dissolution and precipitation processes results in pore volume and structure changes in the subsurface porous media. In this study, the column porosity increased up to 40.3% in the pure dissolution column when no dissolved Al was present in the leachate, whereas up to a 26.5% porosity decrease was found in columns where both dissolution and precipitation were observed because of the presence of Al in the input solution. The porosity change was also confirmed by calculation using the dissolution and precipitation rates and mineral volume changes.

The representation of cloud and precipitation chemistry and subsequent wet deposition of trace constituents in global atmospheric chemistry models is associated with large uncertainties. To improve the simulated trace gas distributions we apply the new submodel SCAV, which includes detailed cloud and precipitation chemistry and present results of the atmospheric chemistry general circulation model ECHAM5/MESSy1. A good agreement with observed wet deposition fluxes for species causing acid rain is obtained. The new scheme enables prognostic calculations of the pH of clouds and precipitation, and these results are also in accordance with observations. We address the influence of detailed cloud and precipitation chemistry on trace constituents based on sensitivity simulations. The results confirm previous results from regional scale and box models, and we extend the analysis to the role of aqueous phase chemistry on the global scale. Some species are directly affected through multiphase removal processes, and many also indirectly through changes in oxidant concentrations, which in turn have an impact on the species lifetime. While the overall effect on tropospheric ozone is relatively small (<10%), regional effects on O3 can reach ~20%, and several important compounds (e.g., H2O2, HCHO) are substantially depleted by clouds and precipitation.

The representation of cloud and precipitation chemistry and subsequent wet deposition of trace constituents in global atmospheric chemistry models is associated with large uncertainties. To improve the simulated trace gas distributions we apply the new submodel SCAV, which includes detailed cloud and precipitation chemistry and present results of the atmospheric chemistry general circulation model ECHAM5/MESSy1. A good agreement with observed wet deposition fluxes for species causing acid rain is obtained. The new scheme enables prognostic calculations of the pH of clouds and precipitation, and these results are also in accordance with observations. We address the influence of detailed cloud and precipitation chemistry on trace constituents based on sensitivity simulations. The results confirm previous results from regional scale and box models, and we extend the analysis to the role of aqueous phase chemistry on the global scale. Some species are directly affected through multiphase removal processes, and many also indirectly through changes in oxidant concentrations, which in turn have an impact on the species lifetime. While the overall effect on tropospheric ozone is relatively small (<10%), regional effects on O3 can reach ≍20%, and several important compounds (e.g., H2O2, HCHO) are substantially depleted by clouds and precipitation.

The purpose of this research is to simulate the operation of the GPM constellation and to evaluate its efficiency in measuring precipitation by comparing the actual precipitation recorded by ground instruments to the precipitation profile obtained by solely utilizing the snapshots taken by the satellites over an area. The GPM constellation consists of one mothership satellite and several drones. It is dynamic in its nature, so that one or more satellites can be added or subtracted from the constellation without significantly altering its functionality. For the time being, six satellites are considered to be part of the GPM constellation: DMSP-F13, DMSP-F14, DMSP-F15, ADEOS-II, AQUA (EOS-PM) and TRMM. The study area is the Rondonia basin in Amazon, Brazil. The ground data set used comes from the LBA experiment, conducted from November 1st 1998 to February 28th 1999. During most of this period, four rain gages networks and the SPOL radar were in operation. The rain gages record rainfall every hour while the SPOL radar takes several snapshots every hour. Due to the orbit characteristics of the satellites, the duration of each visit is small, practically less than a minute. Therefore, in order to obtain comparable measurements, the areal precipitation is estimated using GIS techniques, and then it is disaggregated into one-minute time intervals. The satellites collect one-minute snapshots of this areal precipitation, and after the end of the simulation the snapshots are aggregated in order to reproduce the measured areal precipitation. By comparing the measured areal precipitation with that recorded by the ground instruments, a measure of the constellation's efficiency is acquired.

The region of Valencia in Spain has historically been affected by heavyprecipitation events (HPEs). These HPEs are known to be modulated by the sea surface temperature (SST) of the Balearic Sea. Using an atmosphere-ocean regional climate model, we show that more than 70 % of the HPEs in the region of Valencia present a SST cooling larger than the monthly trend in the Northwestern Mediterranean before the HPEs. This is linked to the breaking of a Rossby wave preceding the HPEs: a ridge-trough pattern at mid-levels centered over western France associated with a low-level depression in the Gulf of Genoa precedes the generation of a cut-off low over southern Spain with a surface depression over the Alboran Sea in the lee of the Atlas. This latter situation is favourable to the advection of warm and moist air towards the Mediterranean Spanish coast, possibly leading to HPEs. The depression in the Gulf of Genoa generates intense northerly (Mistral) to northwesterly (Tramontane/Cierzo) winds. In most cases, these intense winds trigger entrainment at the bottom of the oceanic mixed layer which is a mechanism explaining part of the SST cooling in most cases. Our study suggests that the SST cooling due to this strong wind regime then persists until the HPEs and reduces the precipitation intensity.

The performance of Version 2 of the Flexible Global Ocean-Atmosphere-Land System model (FGOALS-s2) in simulating global monsoon precipitation (GMP) was evaluated. Compared with FGOALS-s1, higher skill in simulating the annual modes of climatological tropical precipitation and interannual variations of GMP are seen in FGOALS-s2. The simulated domains of the northwestern Pacific monsoon (NWPM) and North American monsoon are smaller than in FGOALS-s1. The main deficiency of FGOALS-s2 is that the NWPM has a weaker monsoon mode and stronger negative pattern in spring-fall asymmetric mode. The smaller NWPM domain in FGOALS-s2 is due to its simulated colder SST over the western Pacific warm pool. The relationship between ENSO and GMP is simulated reasonably by FGOALS-s2. However, the simulatedprecipitation anomaly over the South African monsoon region-South Indian Ocean during La Niña years is opposite to the observation. This results mainly from weaker warm SST anomaly over the maritime continent during La Niña years, leading to stronger upper-troposphere (lower-troposphere) divergence (convergence) over the Indian Ocean, and artificial vertical ascent (descent) over the Southwest Indian Ocean (South African monsoon region), inducing local excessive (deficient) rainfall. Comparison between the historical and pre-industrial simulations indicated that global land monsoon precipitation changes from 1901 to the 1970s were caused by internal variation of climate system. External forcing may have contributed to the increasing trend of the Australian monsoon since the 1980s. Finally, it shows that global warming could enhance GMP, especially over the northern hemispheric ocean monsoon and southern hemispheric land monsoon.

This study investigates the resolution dependency of precipitation extremes in an aqua-planet framework. Strong resolution dependency of precipitation extremes is seen over both tropics and extra-tropics, and the magnitude of this dependency also varies with dynamical cores. Moisture budget analyses based on aqua-planet simulations with the Community Atmosphere Model (CAM) using the Model for Prediction Across Scales (MPAS) and High Order Method Modeling Environment (HOMME) dynamical cores but the same physics parameterizations suggest that during precipitation extremes moisture supply for surface precipitation is mainly derived from advective moisture convergence. The resolution dependency of precipitation extremes mainly originates from advective moisture transport in the vertical direction. At most vertical levels over the tropics and in the lower atmosphere over the subtropics, the vertical eddy transport of mean moisture field dominates the contribution to precipitation extremes and its resolution dependency. Over the subtropics, the source of moisture, its associated energy, and the resolution dependency during extremes are dominated by eddy transport of eddies moisture at the mid- and upper-troposphere. With both MPAS and HOMME dynamical cores, the resolution dependency of the vertical advective moisture convergence is mainly explained by dynamical changes (related to vertical velocity or omega), although the vertical gradients of moisture act like averaging kernels to determine the sensitivity of the overall resolution dependency to the changes in omega at different vertical levels. The natural reduction of variability with coarser resolution, represented by areal data averaging (aggregation) effect, largely explains the resolution dependency in omega. The thermodynamic changes, which likely result from non-linear feedback in response to the large dynamical changes, are small compared to the overall changes in dynamics (omega). However, after excluding the

In order to assess to what extent regional climate models (RCMs) yield better representations of climatic states than general circulation models (GCMs) the output of the two model types is usually directly compared with observations and the value added through RCMs has been clearly demonstrated. RCM output is often bias-corrected and in some cases bias correction methods can also be applied to GCMs. The question thus arises what the added value of RCMs in this setup is, i.e. whether bias-corrected RCMs perform better than bias-corrected GCMs. Here we present some first results from such a comparison. We used a stochastic Model Output Statistics (MOS) method, which can be seen as a general version of bias correction, to estimate daily precipitation at 465 UK stations between 1961-2000 using simulatedprecipitation from the RACMO2 and CCLM RCMs and from the ECHAM5 GCM as predictors. The MOS method uses logistic regression to model rainfall occurrence and a Gamma distribution for the wet-day distribution. All model parameters are made linearly dependent on the predictors, i.e. the simulatedprecipitation. The fitting and validation of the statistical model requires the daily, large-scale weather states in the RCM and GCM to represent the actual, historic weather situation. For the RCMs this is achieved by using simulations driven by reanalysis data; RACMO2 is just driven at the boundaries, whereas in CCLM the circulation within the model domain is additionally kept close to the reanalysis through spectral nudging. For the GCM we have used a simulation nudged towards ERA40. The model validation is done in a cross-validation setup and is based on Brier scores for occurrence and quantile scores for the estimated probability distributions. The comparison of the validation skills for the two RCM cases shows some improved skill if spectral nudging is used, indicating that on daily timescales RCMs can generate internal variability that needs to be kept in mind when designing

Precipitation and other hydrologic variables play important roles in river basins. In this study, summer precipitation, evaporation, and water vapor transport from 16 models that have participated in Coupled Model Intercomparison Project Phase 5 (CMIP5) for the Yellow River basin (a water-limited basin) and the Yangtze River basin (an energy-limited basin) over the period 1986-2005 are analyzed and evaluated. The results suggest that most models tend to overestimate precipitation in the Yellow River basin, whereas precipitation in the Yangtze River basin is generally well simulated. Models that overestimate precipitation in the Yellow River basin also simulate evaporation with large positive biases. For water vapor transport, models and reanalysis data concur that both basins are moisture sinks in summer. In addition, models that strongly overestimate precipitation in the Yellow River basin tend to produce strong water vapor convergence in that region, which is likely to be related to the situation that the western Pacific subtropical high (WPSH) simulated by these models strengthens and advances further westward and northward, resulting in stronger water vapor convergence in the Yellow River basin. Moreover, convective precipitation biases simulated by the models are also partially responsible for their total precipitation biases. Finally, summer precipitation and evaporation are negatively correlated in the Yangtze River basin, whereas the relation between these variables is weak in the Yellow River basin. In both basins, precipitation and water vapor convergence are positively correlated, which is well simulated by all models.

Stray electrons can be introduced in heavy ion fusion accelerators as a result of ionization of ambient gas or gas released from walls due to halo-ion impact, or as a result of secondary-electron emission. We summarize here results from several studies of electron-cloud accumulation and effects: (1) Calculation of the electron cloud produced by electron desorption from computed beam ion loss; the importance of ion scattering is shown; (2) Simulation of the effect of specified electron cloud distributions on ion beam dynamics. We find electron cloud variations that are resonant with the breathing mode of the beam have the biggest impact on the beam (larger than other resonant and random variations), and that the ion beam is surprisingly robust, with an electron density several percent of the beam density required to produce significant beam degradation in a 200-quadrupole system. We identify a possible instability associated with desorption and resonance with the breathing mode. (3) Preliminary investigations of a long-timestep algorithm for electron dynamics in arbitrary magnetic fields.

Precipitation projections for the northeast United States and nearby Canada (Northeast) are examined for 15 Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) models. A process-based evaluation of atmospheric circulation features associated with wet Northeast summers is performed to examine whether credibility can be differentiated within the multimodel ensemble. Based on these evaluations, and an analysis of the interannual statistical properties of area-averaged precipitation, model subsets were formed. Multimodel precipitation projections from each subset were compared to the multimodel projection from all of the models. Higher-resolution North American Regional Climate Change Assessment Program (NARCCAP) regional climate models (RCMs) were subjected to a similar evaluation, grouping into subsets, and examination of future projections. CMIP5 models adequately simulate most large-scale circulation features associated with wet Northeast summers, though all have errors in simulating observed sea level pressure and moisture divergence anomalies in the western tropical Atlantic/Gulf of Mexico. Relevant large-scale processes simulated by the RCMs resemble those of their driving global climate models (GCMs), which are not always realistic. Future RCM studies could benefit from a process analysis of potential driving GCMs prior to dynamical downscaling. No CMIP5 or NARCCAP models were identified as clearly more credible, but six GCMs and four RCMs performed consistently better. Among the "Better" models, there is no consistency in the direction of future summer precipitation change. CMIP5 projections suggest that the Northeast precipitation response depends on the dynamics of the North Atlantic anticyclone and associated circulation and moisture convergence patterns, which vary among "Better" models. Even when model credibility cannot be clearly differentiated, examination of simulated processes provides important insights into their evolution under

The Savannah River National Laboratory is in the process of investigating factors suspected of impacting catalytic hydrogen generation in the Chemical Process Cell of the Defense Waste Processing Facility, DWPF. Noble metal catalyzed hydrogen generation in simulation work constrains the allowable acid addition operating window in DWPF. This constraint potentially impacts washing strategies during sludge batch preparation. It can also influence decisions related to the addition of secondary waste streams to a sludge batch. Noble metals have historically been added as trim chemicals to process simulations. The present study investigated the potential conservatism that might be present from adding the catalytic species as trim chemicals to the final sludge simulant versus co-precipitating the noble metals into the insoluble sludge solids matrix. Parallel preparations of two sludge simulants targeting the composition of Sludge Batch 3 were performed in order to evaluate the impact of the form of noble metals. Identical steps were used except that one simulant had dissolved palladium, rhodium, and ruthenium present during the precipitation of the insoluble solids. Noble metals were trimmed into the other stimulant prior to process tests. Portions of both sludge simulants were held at 97 C for about eight hours to qualitatively simulate the effects of long term storage on particle morphology and speciation. The simulants were used as feeds for Sludge Receipt and Adjustment Tank, SRAT, process simulations. The following conclusions were drawn from the simulant preparation work: (1) The first preparation of a waste slurry simulant with co-precipitated noble metals was successful, based on the data obtained. It appears that 99+% of the noble metals were retained in the simulant. (2) Better control of carbonate, hydroxide, and post-wash trim chemical additions is needed before the new method of simulant preparation will be as reproducible as the old method. (3) The two new

comparison with GEV and GP-based approaches, quantile regression approaches thus allow for more flexibility and make full use of all available observational values, no matter if extreme or not. Due to the latter fact, trends in extreme values can be more easily assessed based on shorter time series. However, the question under which conditions and to what extent regression and extreme value theory-based approaches provide consistent results has not yet been fully explored. In this study, we provide a thorough inter-comparison between the recent trends in extreme precipitation events (assessed in terms of daily precipitation sums) from a large set of German weather stations as revealed by the classical (monthly) block maxima method with linearly time-dependent GEV parameters and linear quantile regression of the full time series. For the study period from 1951 to 2006, our main findings are as follows: (1) The spatial patterns of quantile trends for various high (>90%) percentiles and trends in the location parameter of the GEV distribution are qualitatively consistent and exhibit significant correlations, which, however, clearly deviate from an ideal correspondence. (2) In comparison with the trend parameters, the intercepts of the respective linear models for the GEV location parameter and different quantiles exhibit considerably larger mutual correlation values. (3) Quantile regression indicates more stations with strongly positive trends in extreme precipitation than the block maxima method. Moreover, the significance statements provided by the GEV statistics are more conservative than those resulting from quantile regression. Significant upward trends are generally restricted to Southern and Western Germany and are almost completely absent in the Northeastern part of the country. (4) More complex GEV models including linear trends in both location and dispersion parameter need to be considered only for a small subset of all stations (202 out of 2342). In most cases

The Souris River Basin is a 61,000-square-kilometer basin in the Provinces of Saskatchewan and Manitoba and the State of North Dakota. In May and June of 2011, record-setting rains were seen in the headwater areas of the basin. Emergency spillways of major reservoirs were discharging at full or nearly full capacity, and extensive flooding was seen in numerous downstream communities. To determine the probability of future extreme floods and droughts, the U.S. Geological Survey, in cooperation with the North Dakota State Water Commission, developed a stochastic model for simulating Souris River Basin precipitation, evapotranspiration, and natural (unregulated) streamflow. Simulations from the model can be used in future studies to simulate regulated streamflow, design levees, and other structures; and to complete economic cost/benefit analyses.Long-term climatic variability was analyzed using tree-ring chronologies to hindcast precipitation to the early 1700s and compare recent wet and dry conditions to earlier extreme conditions. The extended precipitation record was consistent with findings from the Devils Lake and Red River of the North Basins (southeast of the Souris River Basin), supporting the idea that regional climatic patterns for many centuries have consisted of alternating wet and dry climate states.A stochastic climate simulation model for precipitation, temperature, and potential evapotranspiration for the Souris River Basin was developed using recorded meteorological data and extended precipitation records provided through tree-ring analysis. A significant climate transition was seen around1970, with 1912–69 representing a dry climate state and 1970–2011 representing a wet climate state. Although there were some distinct subpatterns within the basin, the predominant differences between the two states were higher spring through early fall precipitation and higher spring potential evapotranspiration for the wet compared to the dry state.A water

To gain a better understanding of the spatiotemporal distribution of rainfall over the Churchill River basin, this study was undertaken. The research incorporates gridded precipitation data from the Canadian Precipitation Analysis (CaPA) system. CaPA has been developed by Environment Canada and provides near real-time precipitation estimates on a 10 km by 10 km grid over North America at a temporal resolution of 6 hours. The spatial fields are generated by combining forecasts from the Global Environmental Multiscale (GEM) model with precipitation observations from the network of synoptic weather stations. CaPA's skill is highly influenced by the number of weather stations in the region of interest as well as by the quality of the observations. In an attempt to evaluate the performance of CaPA as a function of the density of the weather station network, a dual-stage design algorithm to simulate CaPA is proposed which incorporates generated weather fields. More specifically, we are adopting a controlled design algorithm which is generally known as Observing System Simulation Experiment (OSSE). The advantage of using the experiment is that one can define reference precipitation fields assumed to represent the true state of rainfall over the region of interest. In the first stage of the defined OSSE, a coupled stochastic model of precipitation and temperature gridded fields is calibrated and validated. The performance of the generator is then validated by comparing model statistics with observed statistics and by using the generated samples as input to the WATFLOOD™ hydrologic model. In the second stage of the experiment, in order to account for the systematic error of station observations and GEM fields, representative errors are to be added to the reference field using by-products of CaPA's variographic analysis. These by-products explain the variance of station observations and background errors.

Pollen data collected in Africa at high (Kuruyange, valley swamp, Burundi) and low altitude (Victoria, lake, Uganda; Ngamakala, pond, Congo) showed that after 6 ky before present (BP), pollen of deciduous trees increase their relative percentage, suggesting thus the reduction of the annual amount of precipitation and/or an increase of in the length of the dry season. Until now, pollen-climate transfer functions only investigated mean annual precipitation, due to the absence of modern pollen-assemblage analogs under diversified precipitation regimes. Hence these functions omit the potential effect of a change in precipitation seasonality modifying thus the length of the dry season. In the present study, we use an equilibrium biosphere model (i.e. BIOME3.5) to estimate the sensitivity of equatorial African vegetation, at specific sites, to such changes. Climatic scenarios, differing only in the monthly distribution of the current annual amount of precipitation, are examined at the above three locations in equatorial Africa. Soil characteristics, monthly temperatures and cloudiness are kept constant at their present-day values. Good agreement is shown between model simulations and current biomes assemblages, as inferred from pollen data. To date, the increase of the deciduous forest component in the palaeodata around 6 ky BP has been interpreted as the beginning of a drier climate period. However, our results demonstrate that a change in the seasonal distribution of precipitation could also induce the observed changes in vegetation types. This study confirms the importance of taking into account seasonal changes in the hydrological balance. Palaeoecologists can greatly benefit from the use of dynamic process based vegetation models to acccount for modification of the length of the dry season when they wish to reconstruct vegetation composition or to infer quantitative climate parameters, such as temperature and precipitation, from pollen or vegetation proxy.

Water resources assessments for future climates require meaningful simulations of likely precipitation and evaporation for simulation of flow and derived quantities of interest. Future climate projections using Global Climate Models (GCMs) are commonly used to assess the impacts of global climate change on hydrology and water resources. The reliability of such assessments, however, is questionable due to the various uncertainties present in GCM simulations, such as those associated with model structure, scenario, and initial condition. We present here a new basis for assigning a measure of uncertainty to GCM simulations of precipitation and temperature. Unlike other alternatives which assess overall GCM uncertainty, our approach leads to a unique measure of uncertainty in the variable of interest for each simulated value in space and time. We refer to this as an error model of GCM precipitation and temperature simulations. This is done through estimation of an uncertainty metric, called square root of error variance (SREV), and it involves the following steps: (1) Interpolating GCM outputs to a common spatial grid; (2) Converting the interpolated GCM outputs to percentiles; (3) Estimating SREV for each percentile; and (4) Transforming SREV estimates to time series. The SREV is derived taking into account the model structural, the emission scenario, and the initial condition uncertainty of the simulated value, the full error model being formulated using six GCMs (from the Coupled Model Inter-comparison Project phase 3 (CMIP3) multi-model dataset); three emission scenarios (B1, A1B and A2) and three ensemble runs, with a total of 54 time series representing the period 2001 to 2099. The results reveal that model uncertainty is the main source of error followed by scenario uncertainty. For precipitation, total uncertainty is larger in the tropical region close to the equator and reduces towards the north and south poles. The opposite is true for temperature where

In this study, we used precipitation elasticity index of streamflow to reflect on the sensitivity of streamflow to changes in future precipitation. We estimated precipitation elasticity of streamflow from: (1) observed streamflow and precipitation; (2) simulated streamflow by the VIC model using simulatedprecipitation from a multi-model CMIP5 dataset for the current climate (1970-1999); (3) simulated streamflow using simulatedprecipitation from a multi-model CMIP5 dataset for the future climate (2040-2080) including two different pathways (RCP4.5 and RCP8.5). The hydrological model was calibrated at 1/16 latitude-longitude resolution and the simulated streamflow was routed to the subbasin outlets of interest. We used hydrological model simulations from 1970-1999 and calculated runoff sensitivities for 1980-1999 using observed climate (case 1) and simulated climate (case 2). The runoff sensitivity to long-term (e.g., 20-year) average annual and seasonal changes in precipitation is calculated based on the elasticity of streamflow for reference historical period (1970-1999), which are of importance to reservoir management in the Columbia River basin (case 3). These three cases are compared to assess the effects of forcing by different climate models and different pathways on the precipitation elasticity of streamflow.

Caustic NaNO3 solutions containing dissolved Al were reacted with quartz sand at 89 degrees C to simulate possible reactions between leaked nuclear waste and primary subsurface minerals at the U.S. Department of Energy's Hanford site in Washington. Nitrate-cancrinite began to precipitate onto the quartz after 2-10 days, cementing the grains together. Estimates of the equilibrium constant for the precipitation reaction differ for solutions with 0.1 or 1.0 m OH- (log Keq = 30.4 +/- 0.8 and 36.2 +/- 0.6, respectively). The difference in solubility may be attributable to more perfect crystallinity (i.e., fewer stacking faults) in the higher-pH cancrinite structure. This is supported by electron micrographs of crystal morphology and measured rates of Na volatilization under an electron beam. Precipitate crystallinity may affect radionuclide mobility, because stacking faults in the cancrinite structure can diminish its zeolitic cation exchange properties. The precipitation rate near the onset of nucleation depends on the total Al and Si concentrations in solution. The evolution of experimental Si concentrations was modeled by considering the dependence of quartz dissolution rate on AI(OH)4- activity, cancrinite precipitation, and the reduction of reactive surface area of quartz due to coverage by cancrinite. PMID:11757605

Pollen data collected in Africa at high (Kuruyange, valley swamp, Burundi) and low altitude (Lake Victoria; Ngamakala, pond, Congo) showed that after 6 ky Before Present (BP), pollen of deciduous trees increase their relative percentage, thus suggesting the beginning of a drier climate and/or an increase of the dry season length. Until now, pollen-climate transfer functions only investigated mean annual precipitation, hence omitting the potential effect of a change in precipitation seasonality. In the present study, we use an equilibrium biosphere model (i.e. BIOME3.5) to estimate the sensitivity of equatorial African vegetation to such changes, at specific sites. Climatic scenarios, differing only by the monthly distribution of the current annual amount of precipitations, are tested at the above three locations in equatorial Africa. Soil nature, monthly temperatures and cloudiness are kept constant at their present day values. A good agreement is shown between model simulations and current biomes assemblages, as reconstructed from pollen data. To date, the increase of the deciduous forest component in the palaeodata around 6 ky has been interpreted as the beginning of the drier climate period. However, our results demonstrate that a seasonal change of the precipitation distribution should likely induce such reconstructed changes toward drier vegetation types. This study confirms the necessity of taking into account seasonal changes in the hydrological balance when palaeoecologists wish to reconstruct vegetation composition or to infer quantitative climate parameters, such as temperature and precipitation, from pollen or vegetation proxy.

About 37-50% (w/w) of the heptane asphaltenes from unpyrolyzed residua dissolve in cyclohexane. As pyrolysis progresses, this number decrease to below 15% as coke and toluene insoluble pre-coke materials appear. This solubility measurement can be used after coke begins to form, unlike the flocculation titration, which cannot be applied to multi-phase systems. Currently, the procedure for the isolation of heptane asphaltenes and the determination of the amount of asphaltenes soluble in cyclohexane spans three days. A more rapid method to measure asphaltene solubility was explored using a novel on-column asphaltene precipitation and re-dissolution technique. This was automated using high performance liquid chromatography (HPLC) equipment with a step gradient sequence using the solvents: heptane, cyclohexane, toluene:methanol (98:2). Results for four series of original and pyrolyzed residua were compared with data from the gravimetric method. The measurement time was reduced from three days to forty minutes. The separation was expanded further with the use of four solvents: heptane, cyclohexane, toluene, and cyclohexanone or methylene chloride. This provides a fourth peak which represents the most polar components, in the oil.

Assessment of climate change impacts on water resources is extremely challenging, due to the inherent uncertainties in climate projections using global climate models (GCMs). Three main sources of uncertainties can be identified in GCMs, i.e., model structure, emission scenario, and natural variability. The recently released fifth phase of the Coupled Model Intercomparison Project (CMIP5) includes a number of advances relative to its predecessor (CMIP3), in terms of the spatial resolution of models, list of variables, and concept of specifying future radiative forcing, among others. The question, however, is do these modifications indeed reduce the uncertainty in the projected climate at global and/or regional scales? We address this question by quantifying and comparing uncertainty in precipitation and temperature from 6 CMIP3 and 13 CMIP5 models. Uncertainty is quantified using the square root of error variance, which specifies uncertainty as a function of time and space, and decomposes the total uncertainty into its three constituents. The results indicate a visible reduction in the uncertainty of CMIP5 precipitation relative to CMIP3 but no significant change for temperature. For precipitation, the GCM uncertainty is found to be larger in regions of the world that receive heavy rainfall, as well as mountainous and coastal areas. For temperature, however, uncertainty is larger in extratropical cold regions and lower elevation areas.

The use of a beam of heavy ions to heat a target for the study of warm dense matter physics, high energy density physics, and ultimately to ignite an inertial fusion pellet, requires the achievement of beam intensities somewhat greater than have traditionally been obtained using conventional accelerator technology. The research program described here has substantially contributed to understanding the basic nonlinear intense-beam physics that is central to the attainment of the requisite intensities. Since it is very difficult to reverse intensity dilution, avoiding excessive dilution over the entire beam lifetime is necessary for achieving the required beam intensities on target. The central emphasis in this research has therefore been on understanding the nonlinear mechanisms that are responsible for intensity dilution and which generally occur when intense space-charge-dominated beams are not in detailed equilibrium with the external forces used to confine them. This is an important area of study because such lack of detailed equilibrium can be an unavoidable consequence of the beam manipulations such as acceleration, bunching, and focusing necessary to attain sufficient intensity on target. The primary tool employed in this effort has been the use of simulation, particularly the WARP code, in concert with experiment, to identify the nonlinear dynamical characteristics that are important in practical high intensity accelerators. This research has gradually made a transition from the study of idealized systems and comparisons with theory, to study the fundamental scaling of intensity dilution in intense beams, and more recently to explicit identification of the mechanisms relevant to actual experiments. This work consists of two categories; work in direct support beam physics directly applicable to NDCX and a larger effort to further the general understanding of space-charge-dominated beam physics.

A model of a mixed-mode nutrient recovery reactor is developed for a urine feed, incorporating complex solution thermodynamics, dynamic conservation relations and a power-law kinetic expression for crystal growth from seed crystals. Simulations at nominal operating conditions predict phosphorus recoveries greater than 99%, based on existing process kinetic parameters and operating conditions employed in previously published studies. The overall rate of nutrient recovery depends on the saturation index of the precipitating solid, the available surface area for mass transfer and the feed rate of the limiting constituent ion. Under the conditions considered, the nutrient feed rate appears to be the limiting factor for precipitation. Simulations demonstrate that diurnal feed flow variations of ±50% have a small effect on the rate of nutrient recovery. Overall, the study shows that valuable insights are gained in relation to process performance predictions, which should lead to more confident process design, operation and control. PMID:23787310

The impact of model resolution on the simulation of diurnal variations of precipitation over East Asia during the summer monsoon period of 2006 is investigated by conducting a suite of ensemble simulations of three different cumulus parameterization schemes (CPS), which are Kain-Fritsch, Kain-Fritsch with a modified trigger function, and Simplified Arakawa-Schubert, and the convection-permitting (CP) setting with the Weather Research and Forecasting model. The horizontal resolutions of 50 km, 27 km, and 9 km are applied for each different representation of convection process. Model simulations as a whole are able to mimic the diurnal and semidiurnal cycles with 24 h and 12 h peaks in the morning and the afternoon. However, the simulated afternoon peaks over land are earlier in the CPS runs, while delayed in the CP runs, compared to those observed. The increase of resolution improves the phase and amplitude of diurnal variations in the CP runs due to the explicit representation of the realistic cloud system. In addition, the contribution of nonconvective precipitation from the microphysical process significantly improves the phase of diurnal variations in the CPS runs, especially the afternoon peak over land. The KFtr scheme outperforms other schemes in reproducing the diurnal variations due to the relatively dominant role of nonconvective precipitation. Phase does not change with increasing resolution in the diurnal variations of convective precipitation. Only the modification of the convection scheme, such as the alternative trigger function in the KFtr scheme distinguished from the KF scheme, can make fundamental changes in phase of diurnal variation.

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. In addition, South American meteorology and climate are also made further complicated by ENSO, a powerful coupled ocean-atmosphere phenomenon. Modelling studies in this region have typically resorted to either atmospheric mesoscale or atmosphere-ocean coupled global climate models. The latter offers full physics and high spatial resolution, but it is computationally inefficient typically lack an interactive ocean, whereas the former offers high computational efficiency and ocean-atmosphere coupling, but it lacks adequate spatial and temporal resolution to adequate resolve the complex orography and explicitly simulateprecipitation. Explicit simulation of precipitation is vital in the Central Andes where rainfall rates are light (0.5-5 mm hr-1), there is strong seasonality, and most precipitation is associated with weak mesoscale-organized convection. Recent increases in both computational power and model development have led to the advent of coupled ocean-atmosphere mesoscale models for both weather and climate study applications. These modelling systems, while computationally expensive, include two-way ocean-atmosphere coupling, high resolution, and explicit simulation of precipitation. In this study, we use the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST), a fully-coupled mesoscale atmosphere-ocean modeling system. Previous work has shown COAWST to reasonably simulate the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data when ECMWF interim analysis data were used for boundary conditions on a 27-9-km grid configuration (Outer grid extent: 60.4S to 17.7N and 118.6W to 17.4W).

We found that internal variability is a substantial source of uncertainty for local climatological precipitation in an ensemble of perturbed physics experiments (PPE) in which we also perturbed the atmospheric initial conditions. The ensemble consists of about seventy 50-year long AMIP simulations performed with the GFDL model at 1x1 degree resolution. Our goal is to describe the dependence of the local precipitation climatology to the value of each parameter being perturbed in the ensemble; and we found that a quadratic dependence is appropriate for the entrainment in convective clouds (Fig.1a) with the quadratic term acting to compensate the effect of the linear term: the magnitude of the latter is in fact 20-30% larger and of opposite sign in all major convective areas in the Tropics. About 50% of the grid points show such behavior (Fig.1b) when an ensemble of initial conditions is employed. To assess the impact of internal variability we repeated the analysis using only one run for each parameter value and found that the confidence with which the fitting parameters are established is strongly decreased: a difference in the magnitude of the reconstructed precipitation of about 10-30% is obtained, when precipitation is evaluated at the standard value of the entrainment coefficient (Fig.1c); and the number of grid points in which the null hypothesis of "no quadratic dependence" is rejected halves (Fig.1d). Preliminary results on the joint impact of internal variability and temporal span of the simulations indicate that an increased uncertainty of about 10% occurs when only 20 of the 50 years of simulations are considered. Lastly, in exploring model optimization we found that a PPE often cannot be discerned from the internal variability in a simulation length of 50 years.

The ionosphere is a rich reservoir of charged particles from which a variable fraction is transported to the magnetosphere. An important transport phenomena is the formation of upward ion flow above auroral structure. A primary region of the outflow is not known, but contributions come from polar cap, dayside cusp/cleft region, auroral oval, or even from mid-latitudes. In the past global magnetospheric models and fluid codes were used to simulate large scale ion outflow above, e.g., the polar-cap aurora. However, satellites orbiting at low- altitudes have repeatingly detected localized ion outflow above the auroral oval. Ionosphere-magnetosphere coupling simulations gave first insides into the small-scale dynamics of aurora. The aim of this study is the investigation of coupled plasma and neutral dynamics in smaller scale aurora to explain the generation, structure, and dynamics of vertical ion upstream. We consider auroral electron precipitation at ionospheric heights in a 2-D three fluid ionospheric-magnetospheric coupling code (Otto and Zhu, 2003). Specially we examine the effects of the electron precipitation, heat conduction and heating in field- aligned current through coulomb collisions or turbulence causing: i) electron heating, ii) electron pressure gradients, and iii) upstreaming of ions through a resulting ambipolar electric field. Our first case studies are performed for different boundary conditions and for different auroral electron precipitation parameters (variation in characteristic auroral energy, auroral energy flux and horizontal scale). The results shall clarify how auroral precipitation can drive ions upwards. Finally we discuss the effect of ion drag and the interaction of the upstreaming ions with a stable neutral constituent. Otto, O. and H. Zhu, Fluid plasma simulation of coupled systems: Ionosphere and magnetosphere, Space Plasma Simulation. Edited by J. Buechner, C. Dum, and M. Scholer., Lecture Notes in Physics, vol. 615, p.193

The application of microwave energy for in-container solidification of simulated transuranic contaminated precipitation sludges has been tested. Results indicate volume reductions to 83% are achievable by the continuous feeding of pre-dried sludge into a waste container while applying microwave energy. An economic evaluation was completed showing achievable volume and weight reductions to 87% compared with a current immobilization process for wet sludge. 7 refs., 15 figs., 16 tabs.

As planning continues for manned missions far beyond Low Earth Orbit, a paramount concern remains the flight crew's exposure to galactic cosmic radiation. When humans exit the protective magnetic field of Earth, they become subject to bombardment by highly-reactive heavy charged (HZE) particles. A possible consequence of this two- to three-year-long mission is the onset of radiation-induced leukemia, a disorder with a latency period as short as two to three years. Because data on risk to humans from exposure to HZE particles is non-existent, studies of leukemia in animals are now underway to investigate the relative effectiveness of HZE exposures. Leukemogenesis can result from energy depositions occurring within marrow contained in the trabecular spongiosa. Trabecular spongiosa is found in flat bones and within the ends of long bones, and is characterized by an intricate matrix of interconnected bone tissue forming cavities that house marrow. The microscopic internal dimensions of spongiosa vary between species. As radiation traverses this region, interface-induced dose perturbations that occur at the interfaces between bone and marrow affect the patterns of energy deposition within the region. An aim of this project is to determine the extent by which tissue heterogeneity and microscopic dimensions have on patterns of energy deposition within the trabecular spongiosa. This leads to the development of PATHFIT, a computer code capable of generating simple quadric-based geometric models of trabecular spongiosa for both humans and mice based on actual experimentally-determined internal dimensions of trabecular spongiosa. Following the creation of spongiosa models, focus is placed on the development of HITSPAP, a hybrid Monte Carlo (MC) radiation transport code system that combines capabilities of the MC code PENELOPE and MC code PARTRAC. This code is capable of simulating the transport of HZE particles through accurate models of trabecular spongiosa. The final and

Morocco is located at the extreme north-west of Africa between 20 and 37° N. According to the aridity index of De Martonne classification, Moroccan climate varies from sub-humid in the north to arid in the south. The country has experienced several drought events which have had marked impacts on socio-economic sectors and national economy (1940-1945, 1980-1985, 1994-1995 …). During a dry year, the deficit of rainfall can exceed 60% of the climatological value. Rainfall amounts registered show a negative trend at national and regional scales. The drought seems to become more persistent over time. At the same time, the total number of wet days shows a negative trend revealing an increase in the annual dry day number. Many regions became more arid (According to the aridity index of De Martonne) between 1961 and 2008: namely Oujda, Taza, Kenitra, Rabat, Meknès. In order to evaluate climate change impacts on Moroccan winter precipitation, future climate conditions in Morocco under the SRES scenario A1B, are studied by using two 30-year time-slice simulations performed by the variable resolution configuration of the GCM ARPEGE-Climat. The spatial resolution ranges between 50 and 60 km over the country. This high resolution scenarios exhibit for the period 2021-2050 a change in the precipitation distribution and in extreme events. In particular, the precipitation amounts and the occurrence frequency of wet days will decrease in the scenario on all the fourteen stations considered. In terms of extreme events, the maximum dry spell length increases in nearly all the stations and the frequency of high precipitation events is projected to decrease. The evolution of highest percentiles of precipitation distribution does not go, however, in the same sense everywhere. Assessment of a range of uncertainties due to climate modelling has been done by using present-day and SRES scenario A1B data issued from 10 ENSEMBLES-RCMs. This shows that ARPEGE-Climate results are in the

This study evaluates simulations of precipitation patterns over the Central South-West Asia region (25-40N and 45-75E) by using results from the Atmospheric Model Inter-comparison Project (AMIP). Annual and monthly spatial precipitation fields produced by a subset of 13 currently available AMIP model experiments are evaluated for the region and compared with GPCC (Global Precipitation Climatology Centre) monthly precipitation data for the period of 1979-2001. GPCC precipitation data are available with 0.5 degree resolution and correlate with observational precipitation data with a correlation factor of 0.953. The models show large variations in their ability to capture the seasonal precipitation, although spatial correlations indicate that some of the models simulate the pattern of GPCC precipitation fields fairly well. Some models cannot capture the convective precipitation in the region that occurs during spring (March-April) and fall (Sept-Oct). Relative to the GPCC data most of the models predicted well in winter whereas some models cannot adequately capture the summer (monsoon) precipitation which enters the domain from east. On the spatial scales of the selected region, there is little consistent evidence that points to any specific feature as an indicator of model performance. None of the obvious candidates such as horizontal resolution, convective closure schemes, or land surface schemes are reliable discriminators of a models ability to simulateprecipitation accurately. Horizontal resolution effects are apparent in the inter-mountain region, where high resolution models do better that low resolution models. However, there is not enough evidence to produce reliable simulation on this basis. Correlation coefficients of observed precipitation with model output can be improved by using ensemble averaged precipitation from several models.

Northern South America is identified as one of the most vulnerable regions to be affected by climate change. Furthermore, recent extreme wet seasons over the region have caused diverse socio-economic consequences. Hence, the evaluation of the representation of local climate of rainfall simulations at intra-annual seasonal and inter-annual time scales by the CMIP5 models is urgently required, in order to identify and analyze projections of regional and local climate under a global climate change scenario. Here, we evaluate the ability of seven of the CMIP5 models (selected based on literature review) to represent the seasonal mean precipitation and its inter-annual variability over northern South America. Our results suggest that it is easier for models to reproduce rainfall distribution during boreal summer and fall over both oceans and land, since during these seasons, not only incoming radiation, but also ocean-atmosphere feedbacks over Atlantic and Pacific oceans, locate the ITCZ on the Northern Hemisphere. Conversely, models exhibit the worse simulations of the seasonal mean precipitation during boreal winter and spring, when these processes have opposite effects locating the ITCZ. Our results suggest that the models with a better representation of the oceanic ITCZ and the local low-level jets over northern South America, such as the Choco low-level jet, are able to realistically simulate the main features of seasonal precipitation pattern over northern South America.

The accurate representation of rainfall in models of global climate has been a challenging task for climate modelers owing to its small space and time scales. Quantifying this variability is important for comparing simulations of atmospheric behavior with real time observations. In this regard, this paper compares both the statistical and dynamically forced aspects of precipitation variability simulated by the high-resolution (36 km) Nested Regional Climate Model (NRCM), with satellite observations from the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset and simulations from the Community Atmosphere Model (CAM) at T85 spatial resolution. Six years of rainfall rate data (2000-2005) from within the Tropics (30"S-30"N) have been used in the analysis and results are presented in terms of long-term mean rain rates, amplitude and phase of the annual cycle and seasonal mean maps of precipitation. Our primary focus is on characterizing the annual cycle of rainfall over four land regions of the Tropics namely, the Indian Monsoon, the Amazon, Tropical Africa and the North American monsoon. The lower tropospheric circulation patterns are analyzed in both the observations and the models to identify possible causes for biases in the simulatedprecipitation. The 6-year mean precipitationsimulated by both models show substantial biases throughout the global Tropics with NRCM/CAM systematically underestimating/overestimating rainfall almost everywhere. The seasonal march of rainfall across the equator, following the motion of the sun, is clearly seen in the harmonic vector maps. The timing of peak rainfall (phase) produced by NRCM is in closer agreement with the observations compared to CAM. However like the longtime mean, the magnitude of seasonal mean rainfall is greatly underestimated by NRCM throughout the Tropical land mass. Some of these regional biases can be attributed to erroneous circulation and moisture surpluses/deficits in the lower troposphere in both models

The accurate representation of rainfall in models of global climate has been a challenging task for climate modelers owing to its small space and time scales. Quantifying this variability is important for comparing simulations of atmospheric behavior with real time observations. In this regard, this paper compares both the statistical and dynamically forced aspects of precipitation variability simulated by the high-resolution (36 km) Nested Regional Climate Model (NRCM), with satellite observations from the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset and simulations from the Community Atmosphere Model (CAM) at T85 spatial resolution. Six years of rainfall rate data (2000-2005) from within the Tropics (30°S-30°N) have been used in the analysis and results are presented in terms of long-term mean rain rates, amplitude and phase of the annual cycle and seasonal mean maps of precipitation. Our primary focus is on characterizing the annual cycle of rainfall over four land regions of the Tropics namely, the Indian Monsoon, the Amazon, Tropical Africa and the North American monsoon. The lower tropospheric circulation patterns are analyzed in both the observations and the models to identify possible causes for biases in the simulatedprecipitation. The 6-year mean precipitationsimulated by both models show substantial biases throughout the global Tropics with NRCM/CAM systematically underestimating/overestimating rainfall almost everywhere. The seasonal march of rainfall across the equator, following the motion of the sun, is clearly seen in the harmonic vector maps. The timing of peak rainfall (phase) produced by NRCM is in closer agreement with the observations compared to CAM. However like the long-time mean, the magnitude of seasonal mean rainfall is greatly underestimated by NRCM throughout the Tropical land mass. Some of these regional biases can be attributed to erroneous circulation and moisture surpluses/deficits in the lower troposphere in both

U.S. light crude oil production has steadily declined over the last two decades. However, huge known heavy oil deposits in the North American continent remain largely untapped. In the past 10 years, the API gravity of crude oils has been decreasing by about 0.17% per year, and the sulfur content has been increasing by about 0.027% per year. As the API gravity of crude oil decreases, there will be an urgent need for economically viable new technologies to upgrade the heavy oil to a high API gravity feed stock for the refineries. The Idaho National Engineering Laboratory is investigating an innovative plasma process to upgrade heavy oil and refinery residuum. This paper will present some of the results and the implications of this technology for heavy oil upgrade and conversion.

dynamical downscaling, based on simple PDF skill scores. The measure can assess the full quality of the PDFs and at the same time integrates a flexible manner to weight differently the PDF tails. In this study we apply the referred method to characaterize the PDF added value of a high resolution simulation with the WRF model. Results from a WRF climate simulation centred at the Iberian Penisnula with two nested grids, a larger one at 27km and a smaller one at 9km. This simulation is forced by ERA-Interim. The observational data used covers from rain gauges precipitation records to observational regular grids of daily precipitation. Two regular gridded precipitation datasets are used. A Portuguese grid precipitation dataset developed at 0.2°× 0.2°, from observed rain gauges daily precipitation. A second one corresponding to the ENSEMBLES observational gridded dataset for Europe, which includes daily precipitation values at 0.25°. The analisys shows an important PDF added value from the higher resolution simulation, regarding the full PDF and the extremes. This method shows higher potential to be applied to other simulation exercises and to evaluate other variables.

On 19 February 2001, the Tropical Rainfall Measuring Mission (TRMM) satellite observed complex alongfront variability in the precipitation structure of an intense cold-frontal rainband. The TRMM Microwave Imager brightness temperatures suggested that, compared to the northern and southern ends of the rainband, a greater amount of precipitation ice was concentrated in the middle portion of the rainband where the front bowed out. A model simulation conducted using the fifth-generation Pennsylvania State University National Center for Atmospheric Research (PSU NCAR) Mesoscale Model (MM5) is examined to explain the distribution of precipitation associated with the cold-frontal rainband. The simulation reveals that the enhanced precipitation ice production and the implied mean ascent along the central part of the front were associated with a synergistic interaction between a low-level front and an upper-level front associated with an intrusion of high-PV stratospheric air. The low-level front contributed to an intense bow-shaped narrow cold-frontal rainband (NCFR). The upper-level front was dynamically active only along the central to northern portion of the NCFR, where the upper-level PV advection and Q-vector convergence were most prominent. The enhanced mean ascent associated with the upper-level front contributed to a wide cold-frontal rainband (WCFR) that trailed or overlapped with the NCFR along its central to northern segments. Because of the combination of the forcing from both lower- and upper-level fronts, the ascent was deepest and most intense along the central portion of the front. Thus, a large concentration of precipitation ice, attributed to both the NCFR and WCFR, was produced.

Spectral climate models are distinguished by their representation of variables as finite sums of spherical harmonics, with coefficients computed by an orthogonal projection of the variables onto the spherical harmonics. Representing the surface elevation in this manner results in its contamination by Gibbs-like truncation artifacts, which appear as spurious valleys and mountain chains in the topography. These {open_quotes}Gibbs ripples{close_quotes} are present in the surface topographies of spectral climate models from a number of research institutions. Integrations of the Geophysical Fluid Dynamics Laboratory (GFDL) climate model over a range of horizontal resolutions indicate that the Gibbs ripples lead to spurious, small-scale extrema in the spatial distribution of precipitation. This {open_quotes}cellular precipitation pathology{close_quotes} becomes more pronounced with increasing horizontal resolution, causing a deterioration in the fidelity of simulatedprecipitation in higher resolution models. A method is described for reducing the Gibbs ripples that occur when making an incomplete spherical harmonic expansion of the topography. The new spherical harmonic representations of topography are formed by fitting a nonuniform spherical smoothing spline to geodetic data and found by solving a fixed-point problem. This regularization technique results in less distortion of features such as mountain height and continental boundaries than previous smoothing methods. These new expansions of the topography, when used as a lower boundary surface in the GFDL climate model, substantially diminish the cellular precipitation pathology and produce markedly more realistic simulations of precipitation. These developments make the prospect of using higher resolution spectral models for studies of regional hydrologic climate more attractive. 34 refs., 11 figs., 1 tab.

A regional scale model, LAMPS (Limited Area Mesoscale Prediction System), is used to investigate cloud and precipitation structure that accompanied a short wave system during a portion of GALE IOP-2. A comparison of satellite imagery and model fields indicates that much of the large mesoscale organization of condensation has been captured by the simulation. In addition to reproducing a realistic phasing of two baroclinic zones associated with a split cold front, a reasonable simulation of the gross mesoscale cloud distribution has been achieved.

Aerodynamic drag contributes to a considerable amount of energy loss of heavy vehicles. To reduce the energy loss, drag reduction devices such as side skirts and boat tails, are often installed to the side and the rear of a heavy vehicle. In the present study, turbulent flow around a heavy vehicle with realistic geometric details is simulated using large-eddy simulation (LES), which is capable of providing unsteady flow physics responsible for aerodynamic in sufficient detail. Flow over a heavy vehicle with and without a boat tail and side skirts as drag reduction devices is simulated. The simulation results are validated against accompanying in-house experimental measurements. Effects of a boat tail and side skirts on drag reduction are discussed in detail. Supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) Grant NTIS 1615007940.

While runoff is often a first-order control on water quality, runoff generation processes and pathways can vary widely between catchments. Credible simulations of solute and pollutant transport in surface waters are dependent on models which facilitate appropriate representations of perceptual models of the runoff generation process. With a few exceptions, models used in solute transport simulations enforce a single, potentially inappropriate representation of the runoff generation process. Here, we present a flexible, semi-distributed landscape scale rainfall-runoff model suitable for simulating a broad range of user-specified perceptual models of runoff generation and stream flow occurring in different climatic regions and landscape types. PERSiST, the Precipitation, Evapotranspiration and Runoff Simulator for Solute Transport; is designed for simulating present day conditions and projecting possible future effects of climate or land use change on runoff, catchment water storage and solute transport. PERSiST has limited data requirements and is calibrated using observed time series of precipitation, air temperature and runoff at one or more points in a river network. Here, we present a first application of the model to the Thames River in the UK and describe a Monte Carlo tool for parameter optimization and sensitivity analysis.

The low latitude boundary of the proton aurora (known as the Isotropy Boundary or IB) marks an important boundary between empty and full downgoing loss cones. There is significant evidence that the IB maps to a region in the magnetosphere where the ion gyroradius becomes comparable to the local field line curvature. However, the location of the IB in the magnetosphere remains in question. In this paper, we show simulated proton precipitation derived from the Field Line Curvature (FLC) model of proton scattering and a global magnetohydrodynamic simulation during two substorms. The simulated proton precipitation drifts equatorward during the growth phase, intensifies at onset and reproduces the azimuthal splitting published in previous studies. In the simulation, the pre-onset IB maps to 7-8 RE for the substorms presented and the azimuthal splitting is caused by the development of the substorm current wedge. The simulation also demonstrates that the central plasma sheet temperature can significantly influence when and where the azimuthal splitting takes place.

A Regional Climate Model (RCM), MM5 (the Fifth Generation Pennsylvania State University/National Center for Atmospheric Research mesoscale model), is used to simulate summer precipitation in Central Alberta. MM5 was set up with a one-way, three-domain nested framework, with domain resolutions of 27, 9, and 3 km, respectively, and forced with ERA-Interim reanalysis data of ECMWF (European Centre for Medium-Range Weather Forecasts). The objective is to develop high resolution, grid-based Intensity-Duration-Frequency (IDF) curves based on the simulated annual maximums of precipitation (AMP) data for durations ranging from 15-min to 24-h. The performance of MM5 was assessed in terms of simulated rainfall intensity, precipitable water, and 2-m air temperature. Next, the grid-based IDF curves derived from MM5 were compared to IDF curves derived from six RCMs of the North American Regional Climate Change Assessment Program (NARCCAP) set up with 50-km grids, driven with NCEP-DOE (National Centers for Environmental Prediction-Department of Energy) Reanalysis II data, and regional IDF curves derived from observed rain gauge data (RG-IDF). The analyzed results indicate that 6-h simulatedprecipitable water and 2-m temperature agree well with the ERA-Interim reanalysis data. However, compared to RG-IDF curves, IDF curves based on simulatedprecipitation data of MM5 are overestimated especially for IDF curves of 2-year return period. In contract, IDF curves developed from NARCCAP data suffer from under-estimation and differ more from RG-IDF curves than the MM5 IDF curves. The over-estimation of IDF curves of MM5 was corrected by a quantile-based, bias correction method. By dynamically downscale the ERA-Interim and after bias correction, it is possible to develop IDF curves useful for regions with limited or no rain gauge data. This estimation process can be further extended to predict future grid-based IDF curves subjected to possible climate change impacts based on climate

The fifth phase of the Coupled Model Intercomparison Project (CMIP5) is the most recent coordinated experiment of global climate modeling. Compared to its predecessor CMIP3, the fifth phase of the homonymous experiment—CMIP5 involves a greater number of GCMs, run at higher resolutions with more complex components. Here we use daily GCM data from both projects to test their efficiency in representing precipitation and temperature parameters with the use of a state of the art high resolution gridded global dataset for land areas and for the period 1960-2005. Two simple metrics, a comprehensive histogram similarity metric based on the match of simulated and observed empirical pdfs and a metric for the representation of the annual cycle were employed as performance indicators. The metrics were used to assess the skill of each GCM at the entire spectrum of precipitation and temperature pdfs but also for the upper and lower tails of it. Results are presented globally and regionally for 26 land regions that represent different climatic regimes, covering the total earth's land surface except for Antarctica. Compared to CMIP3, CMIP5 models perform better in simulatingprecipitation including relatively intense events and the fraction of wet days. For temperature the improvement is not as clear except for the upper and lower hot and cold events of the distribution. The agreement of model simulations is also considerably increased in CMIP5. Substantial improvement in intense precipitation is observed over North Europe, Central and Eastern North America and North East Europe. Nevertheless, in both ensembles some models clearly perform better than others from a histogram similarity point of view. The derived skill score metrics provide essential information for impact studies based on global or regional land area multi-model ensembles.

We investigate future changes in the annual cycle of heavy daily precipitation events across the British Isles in the periods 2021-2060 and 2061-2100, relative to present day climate. Twelve combinations of regional and global climate models forced with the A1B scenario are used. The annual cycle is modelled as an inhomogeneous Poisson process with sinusoidal models for location and scale parameters of the generalized extreme value distribution. Although the peak times of the annual cycle vary considerably between projections for the 2061-2100 period, a robust shift towards later peak times is found for the south-east, while in the north-west there is evidence for a shift towards earlier peak times. In the remaining parts of the British Isles no changes in the peak times are projected. For 2021-2060 this signal is weak. The annual cycle’s relative amplitude shows no robust signal, where differences in projected changes are dominated by global climate model differences. The relative contribution of anthropogenic forcing and internal climate variability to changes in the relative amplitude cannot be identified with the available ensemble. The results might be relevant for the development of adequate risk-reduction strategies, for insurance companies and for the management and planning of water resources.

This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling (COSMO) model. Six intensive observation periods of the HOPE (HD(CP)2 Observational Prototype Experiment) measurement campaign conducted in spring 2013 and 1 summer day of the same year are simulated. By means of a series of grid-refinement resolution tests (horizontal grid spacing 2.8, 1 km, 500, and 250 m), the applicability of the COSMO model to represent real weather events in the gray zone, i.e., the scale ranging between the mesoscale limit (no turbulence resolved) and the large-eddy simulation limit (energy-containing turbulence resolved), is tested. To the authors' knowledge, this paper presents the first non-idealized COSMO simulations in the peer-reviewed literature at the 250-500 m scale. It is found that the kinetic energy spectra derived from model output show the expected -5/3 slope, as well as a dependency on model resolution, and that the effective resolution lies between 6 and 7 times the nominal resolution. Although the representation of a number of processes is enhanced with resolution (e.g., boundary-layer thermals, low-level convergence zones, gravity waves), their influence on the temporal evolution of precipitation is rather weak. However, rain intensities vary with resolution, leading to differences in the total rain amount of up to +48 %. Furthermore, the location of rain is similar for the springtime cases with moderate and strong synoptic forcing, whereas significant differences are obtained for the summertime case with air mass convection. Domain-averaged liquid water paths and cloud condensate profiles are used to analyze the temporal and spatial variability of the simulated clouds. Finally, probability density functions of convection-related parameters are analyzed to investigate their dependance on model resolution and their impact on cloud formation and subsequent precipitation.

Calcium carbonate is a secondary mineral precipitate influencing zero valent iron (ZVI) barrier reactivity and hydraulic performance. We conducted column experiments to investigate electrical signatures resulting from concurrent CaCO{sub 3} and iron oxides precipitation under simulated field geochemical conditions. We identified CaCO{sub 3} as a major mineral phase throughout the columns, with magnetite present primarily close to the influent based on XRD analysis. Electrical measurements revealed decreases in conductivity and polarization of both columns, suggesting that electrically insulating CaCO{sub 3} dominates the electrical response despite the presence of electrically conductive iron oxides. SEM/EDX imaging suggests that the electrical signal reflects the geometrical arrangement of the mineral phases. CaCO{sub 3} forms insulating films on ZVI/magnetite surfaces, restricting charge transfer between the pore electrolyte and ZVI particles, as well as across interconnected ZVI particles. As surface reactivity also depends on the ability of the surface to engage in redox reactions via charge transfer, electrical measurements may provide a minimally invasive technology for monitoring reactivity loss due to CaCO{sub 3} precipitation. Comparison between laboratory and field data shows consistent changes in electrical signatures due to iron corrosion and secondary mineral precipitation.

Bias-correction methods applied to monthly temperature and precipitation data simulated by multiple General Circulation Models (GCMs) are evaluated in this study. Although various methods have been proposed recently, an intercomparison among them using multiple GCM simulations has seldom been reported. Moreover, no previous methods have addressed the issue how to adequately deal with the changes of the statistics of bias-corrected variables from the historical to future simulations. In this study, a new method which conserves the changes of mean and standard deviation of the uncorrected model simulation data is proposed, and then five previous bias-correction methods as well as the proposed new method are intercompared by applying them to monthly temperature and precipitation data simulated from 12 GCMs in the Coupled Model Intercomparison Project (CMIP3) archives. Parameters of each method are calibrated by using 1948-1972 observed data and validated in the 1974-1998 period. These methods are then applied to the GCM future simulations (2073-2097) and the bias-corrected data are intercompared. For the historical simulations, negligible difference can be found between observed and bias-corrected data. However, the differences in future simulations are large dependent on the characteristics of each method. The new method successfully conserves the changes in the mean, standard deviation and the coefficient of variation before and after bias-correction. The differences of bias-corrected data among methods are discussed according to their respective characteristics. Importantly, this study classifies available correction methods into two distinct categories, and articulates important features for each of them.

An inherent difficulty in the ability of global climate models to accurately simulateprecipitation lies in the use of a large time step, Δt (usually 30 minutes), to solve the governing equations. Since microphysical processes are characterized by small time scales compared to Δt, finite difference approximations used to advance microphysics equations suffer from numerical instability and large time truncation errors. With this in mind, the sensitivity of precipitationsimulated by the atmospheric component of CESM, namely the Community Atmosphere Model (CAM 5.1), to the microphysics time step (τ) is investigated. Model integrations are carried out for a period of five years with a spin up time of about six months for a horizontal resolution of 2.5 × 1.9 degrees and 30 levels in the vertical, with Δt = 1800 s. The control simulation with τ = 900 s is compared with one using τ = 300 s for accumulated precipitation and radi- ation budgets at the surface and top of the atmosphere (TOA), while keeping Δt fixed. Our choice of τ = 300 s is motivated by previous work on warm rain processes wherein it was shown that a value of τ around 300 s was necessary, but not sufficient, to ensure positive definiteness and numerical stability of the explicit time integration scheme used to integrate the microphysical equations. However, since the entire suite of microphysical processes are represented in our case, we suspect that this might impose additional restrictions on τ. The τ = 300 s case produces differences in large-scale accumulated rainfall from the τ = 900 s case by as large as 200 mm, over certain regions of the globe. The spatial patterns of total accumulated precipitation using τ = 300 s are in closer agreement with satellite observed precipitation, when compared to the τ = 900 s case. Differences are also seen in the radiation budget with the τ = 300 (900) s cases producing surpluses that range between 1-3 W/m2 at both the TOA and surface in the global

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model during the South China Sea Monsoon Experiment (SCSMEX) is compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) radiation and cloud retrievals. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. Mesoscale organization is adequately simulated except when environmental wind shear is very weak. The partitions between convective and stratiform rain are also close to TMI and PR classification. However, the model simulated rain spectrum is quite different from either TMI or PR measurements. The model produces more heavy rains and light rains (less than 0.1 mm/hr) than the observations. The model also produces heavier vertical hydrometer profiles of rain, graupel when compared with TMI retrievals and PR radar reflectivity. Comparing GCE simulated OLR and cloud properties with CERES measurements found that the model has much larger domain averaged OLR due to smaller total cloud fraction and a much skewed distribution of OLR and cloud top than CERES observations, indicating that the model's cloud field is not wide spread, consistent with the model's precipitation activity. These results will be used as guidance for improving the model's microphysics.

The choice of the microwave frequency is of considerable importance for precipitating system observations by airborne radar. Currently, these radars operate at X-band (f = 10 GHz), although other frequency bands, may be used jointly or not. Since the measured reflectivity Zm is f-depending, different physical information about precipitating systems could be obtained. Herein, a comparison of reflectivity fields at different frequency bands is presented. A realistic and flexible model of precipitating systems is presented and simulations of airborne radar observations are performed. Simulated reflectivity fields are degraded as/increases because of Mie effects and microwave attenuation. At S, C and X-bands, attenuation is weak and Mie effects slightly increase the backscattered signal such that they can compensate attenuation at X and Ku bands. The Ka and W-bands suffer from a strong attenuation and significant Mie effects which seriously alter Zm-fields. For a squall line, the closer convective tower hides the farther ones, which is problematic for a pilot to estimate hazard at long distance. In addition, because hail is the main meteorological hazard for civil aviation, hail-rain discrimination is discussed and clarified for convective systems. It appears that S, C, and X-bands are the best ones, but the significant size of antenna used is prohibitive. Higher frequencies are more difficult to use on civil aviation due to high ambiguities and a too strongly attenuated microwave signal.

In the warm season in East Asia, rather larger amount of precipitation is brought of the midlatitude region in the world by the great contribution of "heavy rainfall days"(e.g., with the daily precipitation more than 50 mm). Especially, this is remarkably found in the mature stage of the Meiyu/Baiu season in the region from Central China to the western part of the Japan Islands. However, although the total precipitation and the contribution of the "heavy rainfall days" to it in the eastern part of the Japan Islands during that season are not so large than in the western Japan, the total precipitation from the Baiu season to midsummer there is still considerable compared to that in the other midlatitude regions in the world such as Europe. As such, our group (Matsumoto et al.;EGU2014-4772-1)has already reported the rainfall characteristics and large-scale atmospheric fields on the "heavy rainfall days" in the mature stage of the Baiu season (16 June ~ 15 July) at Tokyo in the eastern part of the Japan Islands, based on the daily and the hourly precipitation data from 1971 to 2010. They revealed that, the half of the "heavy rain days" at Tokyo were related directly to the typhoons even in the Baiu season. In addition, in the half of the "heavy rain days" there the total daily rainfall was contributed to mainly by the "moderate rainfall" with the hourly precipitation less than 10 mm. Succeeding to the above report, this study firstly examined the rainfall features and the atmospheric fields for the other patterns of the "heavy rain days" at Tokyo, although the appearance frequency was low (3cases). In these cases, although the synoptic situations were rather different among each other, the they seem to occur under the situation of relatively small zonal scale systems associated with the great meander of upper-level westerly(the cold vortex was also found to the northern area in the two cases). Next, the similar climatological analyses to Matsumoto et al.(EGU2014) were

The ability to accurately model precipitating electron distributions is crucial for understanding magnetosphere-ionosphere-thermosphere coupling processes. We use the magnetically and electrically self-consistent Rice Convection Model-Equilibrium (RCM-E) of the inner magnetosphere to assess how well different electron loss models can account for observed electron fluxes during the large 10 August 2000 magnetic storm. The strong pitch angle scattering rate produces excessive loss on the morning and dayside at geosynchronous orbit (GEO) compared to what is observed by a Los Alamos National Laboratory satellite. RCM-E simulations with parameterized scattering due to whistler chorus outside the plasmasphere and hiss inside the plasmasphere are able to account simultaneously for trapped electron fluxes at 1.2 keV to ~100 keV observed at GEO and for precipitating electron fluxes and electron characteristic energies in the ionosphere at 833 km measured by the NOAA 15 satellite.

The objective of this paper is to identify better performing Coupled Model Intercomparison Project phase 3 (CMIP3) global climate models (GCMs) that reproduce grid-scale climatological statistics of observed precipitation and temperature for input to hydrologic simulation over global land regions. Current assessments are aimed mainly at examining the performance of GCMs from a climatology perspective and not from a hydrology standpoint. The performance of each GCM in reproducing the precipitation and temperature statistics was ranked and better performing GCMs identified for later analyses. Observed global land surface precipitation and temperature data were drawn from the Climatic Research Unit (CRU) 3.10 gridded data set and re-sampled to the resolution of each GCM for comparison. Observed and GCM-based estimates of mean and standard deviation of annual precipitation, mean annual temperature, mean monthly precipitation and temperature and Köppen-Geiger climate type were compared. The main metrics for assessing GCM performance were the Nash-Sutcliffe efficiency (NSE) index and root mean square error (RMSE) between modelled and observed long-term statistics. This information combined with a literature review of the performance of the CMIP3 models identified the following better performing GCMs from a hydrologic perspective: HadCM3 (Hadley Centre for Climate Prediction and Research), MIROCm (Model for Interdisciplinary Research on Climate) (Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change), MIUB (Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model and Data group), MPI (Max Planck Institute for Meteorology) and MRI (Japan Meteorological Research Institute). The future response of these GCMs was found to be representative of the 44 GCM ensemble members which confirms that the selected GCMs are reasonably

An attempt is made to examine the role of Anatolian and Caucasus mountain ranges in the precipitation distribution over the Black Sea region and to clarify the dynamical and physical mechanisms responsible for precipitation distribution over the region. Existence of a complex topography in the southern and eastern part of the Black Sea region makes it an important region for cyclogenesis. In this study the effect of Anatolian and Caucasus Mountains on the precipitating synoptic systems forming over the Black Sea are investigated. To this end, the Weather Research and Forecasting (WRF) model at 15-km horizontal grid spacing has been used to evaluate the lifetime of a low pressure system that was accompanied with heavyprecipitation on 14 March 2009 over the coastal region of the Black Sea. Two experiments were conducted. In the control experiment (CTL), the topographical features of the region were retained. In the sensitivity experiment (EXP), the Anatolian and Caucasus mountain ranges were removed. It is found that in the EXP, some fields including vertical motion, relative vorticity, humidity, geopotential height in low level, cloud water content and precipitation distribution in the region undergo significant changes. As such, in the EXP, the vorticity, and the cut-off low system over the Black Sea intensified. It is also seen that, under favorable conditions for precipitation occurrence, the precipitation intensity in the south and east coasts of the Black Sea decreased and the region of maximum precipitation shifted toward the "Sea of Azov" region, in the direction of the surface southerly winds.

A growing body of literature suggests that human-induced climate change may cause significant changes in precipitation patterns, which could in turn influence future flood levels and frequencies and water supply and management practices. Although climate models produce full three-dimensional simulations of precipitation, analyses of model precipitation have focused either on time-averaged distributions or on individual timeseries with no spatial information. We describe here a new approach based on identifying and characterizing individual rainstorms in either data or model output. Our approach enables us to readily characterize important spatio-temporal aspects of rainstorms including initiation location, intensity (mean and patterns), spatial extent, duration, and trajectory. We apply this technique to high-resolution precipitation over the continental U.S. both from radar-based observations (NCEP Stage IV QPE product, 1-hourly, 4 km spatial resolution) and from model runs with dynamical downscaling (WRF regional climate model, 3-hourly, 12 km spatial resolution). In the model studies we investigate the changes in storm characteristics under a business-as-usual warming scenario to 2100 (RCP 8.5). We find that in these model runs, rainstorm intensity increases as expected with rising temperatures (approximately 7%/K, following increased atmospheric moisture content), while total precipitation increases by a lesser amount (3%/K), consistent with other studies. We identify for the first time the necessary compensating mechanism: in these model runs, individual precipitation events become smaller. Other aspects are approximately unchanged in the warmer climate. Because these spatio-temporal changes in rainfall patterns would impact regional hydrology, it is important that they be accurately incorporated into any impacts assessment. For this purpose we have developed a methodology for producing scenarios of future precipitation that combine observational data and

By explicitly resolving cloud-scale processes with embedded two-dimensional (2-D) cloud-resolving models (CRMs), superparameterized global atmospheric models have successfully simulated various atmospheric events over a wide range of time scales. Up to now, however, such models have not included the effects of topography on the CRM grid scale. We have used both 3-D and 2-D CRMs to simulate the effects of topography with prescribed "large-scale" winds. The 3-D CRM is used as a benchmark. The results show that the mean precipitation can be simulated reasonably well by using a 2-D representation of topography as long as the statistics of the topography such as the mean and standard deviation are closely represented. It is also shown that the use of a set of two perpendicular 2-D grids can significantly reduce the error due to a 2-D representation of topography.

In this study we have investigated the role of domain settings and model's physics in simulating two extreme precipitation events. Four regional climate models, all driven with a re-analysis dataset were used to create an ensemble of 61 high-resolution simulations by varying physical parameterization schemes, domain sizes, nudging and nesting techniques. The two discussed events are three-day time slices taken from approximately 15-months long climate simulations. The results show that dynamical downscaling significantly improves the spatial characteristics such as correlation, variability as well as location and intensity of maximum precipitation. Spatial variability, which is underestimated by most of the simulations can be improved by choosing suitable vertical resolution, convective and microphysics scheme. The results further suggest that for studies focusing on extreme precipitation events relatively small domains or nudging could be advantageous. However, a final conclusion on this issue would be premature, since only two extreme precipitation events are considered.

In this study we have investigated the role of domain settings and model's physics in simulating two extreme precipitation events. Four regional climate models, all driven with a re-analysis dataset were used to create an ensemble of 61 high-resolution simulations by varying physical parameterization schemes, domain sizes, nudging and nesting techniques. The two discussed events are three-day time slices taken from approximately 15-months long climate simulations. The results show that dynamical downscaling significantly improves the spatial characteristics such as correlation, variability as well as location and intensity of maximum precipitation. Spatial variability, which is underestimated by most of the simulations can be improved by choosing suitable vertical resolution, convective and microphysics scheme. The results further suggest that for studies focusing on extreme precipitation events relatively small domains or nudging could be advantageous. However, a final conclusion on this issue would be premature, since only two extreme precipitation events are considered.

We analyze simulations of the global climate performed at a range of spatial resolutions to assess the effects of horizontal spatial resolution on the ability to simulateprecipitation in the continental United States. The model investigated is the CCM3 general circulation model. We also preliminarily assess the effect of replacing cloud and convective parameterizations in a coarse-resolution (T42) model with an embedded cloud-system resolving model (CSRM). We examine both spatial patterns of seasonal-mean precipitation and daily-timescale temporal variability of precipitation in the continental United States. For DJF and SON, high-resolution simulations produce spatial patterns of seasonal-mean precipitation that agree more closely with observed precipitation patterns than do results from the same model (CCM3) at coarse resolution. However, in JJA and MAM, there is little improvement in spatial patterns of seasonal-mean precipitation with increasing resolution, particularly in the Southeast. This is owed to the dominance of convective (i.e., parameterized) precipitation in these two seasons. We further find that higher-resolution simulations have more realistic daily precipitation statistics. In particular, the well-known tendency at coarse resolution to have too many days with weak precipitation and not enough intense precipitation is partially eliminated in higher-resolution simulations. However, even at the highest resolution examined here (T239), the simulated intensity of the mean and of high-percentile daily precipitation amounts is too low. This is especially true in the Southeast, where the most extreme events occur. A new GCM, in which a cloud-resolving model (CSRM) is embedded in each grid cell and replaces convective and stratiform cloud parameterizations, solves this problem, and actually produces too much precipitation in the form of extreme events. However, in contrast to high-resolution versions of CCM3, this model produces little improvement in

A simplified approach is presented for assessing the microwave response to the initial melting of realistically-shaped ice particles. This paper is divided into two parts: (1) a description of the Single Particle Melting Model (SPMM): a heuristic melting simulation for ice-phase precipitation particles of any shape or size. SPMM is applied to two simulated aggregate snow particles, simulating melting up to 0.15 melt fraction by mass; and (2) the computation of the single-particle microwave scattering and extinction properties these hydrometeors, using the discrete dipole approximation (via DDSCAT), at the following selected frequencies: 13.4, 35.6, 94.0 GHz for radar applications; and 89, 165.0 and 183.31 GHz for radiometer applications. These selected frequencies are consistent with current microwave remote sensing platforms, such as CloudSat and the Global Precipitation Measurement (GPM) mission. Comparisons with calculations using variable-density spheres indicate significant deviations in scattering and extinction properties throughout the initial range of melting (liquid volume fractions less than 0.15). Integration of the single-particle properties over an exponential particle-size distribution provides additional insight into idealized radar reflectivity and passive microwave brightness temperature sensitivity to variations in size/mass, shape, melt fraction, and particle orientation.

A simplified approach is presented for assessing the microwave response to the initial melting of realistically shaped ice particles. This paper is divided into two parts: (1) a description of the Single Particle Melting Model (SPMM), a heuristic melting simulation for ice-phase precipitation particles of any shape or size (SPMM is applied to two simulated aggregate snow particles, simulating melting up to 0.15 melt fraction by mass), and (2) the computation of the single-particle microwave scattering and extinction properties of these hydrometeors, using the discrete dipole approximation (via DDSCAT), at the following selected frequencies: 13.4, 35.6, and 94.0 GHz for radar applications and 89, 165.0, and 183.31 GHz for radiometer applications. These selected frequencies are consistent with current microwave remote-sensing platforms, such as CloudSat and the Global Precipitation Measurement (GPM) mission. Comparisons with calculations using variable-density spheres indicate significant deviations in scattering and extinction properties throughout the initial range of melting (liquid volume fractions less than 0.15). Integration of the single-particle properties over an exponential particle size distribution provides additional insight into idealized radar reflectivity and passive microwave brightness temperature sensitivity to variations in size/mass, shape, melt fraction, and particle orientation.

Porosity and permeability of reservoirs are key parameters for an economical use of hot water from geothermal installations and can be significantly reduced by precipitation of minerals, such as anhydrite. The borehole Allermöhe 1 near Hamburg (Germany) represents a failed attempt of geothermal heat mining due to anhydrite precipitation (Baermann et al. 2000). For a risk assessment of future boreholes it is essential to understand how and when anhydrite cementation occurred under reservoir conditions. From core samples of the Allermöhe borehole it was determined that anhydrite precipitation took place in regions of relatively high porosity while regions of low porosity remained uncemented (Wagner et al. 2005). These findings correspond to the fact that e.g. halite precipitation in porous media is found only in relatively large pores (Putnis and Mauthe 2001). This study and others underline that pore size controls crystallization and that it is therefore necessary to establish a relation between pore size and nucleation. The work presented here is based on investigations of Emmanuel and Berkowitz (2007) who present such a relation by applying a thermodynamic approach. However this approach cannot explain the heterogeneous precipitation observed in the Allermöhe core samples. We chose an advanced approach by considering electric system properties resulting in another relation between pore size and crystallization. It is well known that a high fluid supersaturation can be maintained in porous rocks (Putnis and Mauthe 2001). This clearly indicates that a supersaturation threshold exists exceeding thermodynamic equilibrium considerably. In order to quantify spatially heterogeneous anhydrite cementation a theoretical approach was chosen which considered the electric interaction between surface charges of the matrix and calcium and sulphate ions in the fluid. This approach was implemented into the numerical code SHEMAT (Clauser 2003) and used to simulate anhydrite

The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer heating.

About 1200 GPS sites in the westernmost United States are used to weigh changes in surface water as a function of location from 2006 to 2015. The effect of known changes in water in artificial reservoirs is removed, allowing changes in the total of snow, soil moisture, and mountain fracture groundwater to be inferred from GPS. In this study water changes inferred from GPS are placed into the context of complementary InSAR and GRACE data. The southern Central Valley (the San Joaquin Valley and Tulare Basin) is subsiding at spectacular rates of 0.01 m/yr to 0.2 m/yr in response to groundwater management. We construct an elastic model of groundwater change of the southern Central Valley, using GRACE as the basis of total groundwater loss and InSAR to infer the lateral distribution of that groundwater loss. This elastic model of Central Valley groundwater loss is removed from the GPS displacements. Because snow in California is insignificant in October, and because changes in soil moisture between successive autumns are small, we can infer changes in Sierra Nevada mountain fracture groundwater to be: -19 km3 during drought from 2006 to 2009, +35 km3 during heavyprecipitation from 2009 to 2011, and -38 km3 during drought from 2011 to 2014 (start and end times are all in October). We infer changes in Sierra Nevada mountain groundwater to be playing an important role in modulating Central Valley groundwater loss. Total water in the Sierra Nevada recovered by 16 km3 from October 2014 to April 2015, but water is being lost again in summer 2015.

The evolution of the strengthening precipitate in a precipitation-hardening alloy, such as the gamma prime ( γ') phase in Ni-base superalloys, during heat treating and welding can affect the resultant mechanical properties significantly. Computational kinetics simulation can be a useful tool for understanding and controlling of such evolution. The present study was conducted to simulate the γ' precipitation and dissolution during aging and welding of the recently developed Ni-base superalloy 718plus using the PanPrecipitation module of the Pandat software along with available thermodynamic and kinetic databases. The purpose was to demonstrate the application of such software and databases to materials processing including heat treating and welding. The variations in the volume fraction, average precipitation size, and number density of γ' with time during aging and welding were calculated. The calculated results under aging condition agreed well with the available experimental data, while those under welding also predicted the correct trend.

Although H2O is not very soluble in supercritical CO2, a continuous stream of CO2 injected into a formation, will cause a region around the injection well to dry out. As the water of the formation brine is continuously evaporated into the CO2, the irreducible water saturation may attain practically zero. Enhanced injectivity is the result of this process in a low salinity brine environment. In formations saturated with highly saline brine (e.g. Northern German Basin) the outcome is opposite: injectivity is impaired. In this case, the brine becomes supersaturated as continuously H2O evaporates into the CO2 phase and salt (halite) precipitates in the pores. The porosity and permeability diminish, which can lead to the loss of a well. We present simulations of these processes as an example of pre-injection study for a CO2 injection and storage site. The simulation tool consists of a commercial compositional code used extensively in the oil and gas industry to simulate the flow of multiple phases (oil, water, gas) in porous or fractured media. The mutual solubility of CO2 and H2O with a correction for salinity is implemented as described in Spycher and Pruess (2005). The brine salinity is adjusted accordingly until the saturation threshold is reached and halite is precipitated. The distribution of precipitation in the reservoir depends not only of the relationship between permeability change as a function of porosity change, but also on the relative permeability curves for the CO2-brine system. Therefore it is essential to establish relative permeability curves in the laboratory, as well as to obtain a relationship between porosity change and permeability variation with precipitation by laboratory experiments on cores to obtain meaningful results from numerical simulations. References Spycher N. and Pruess, K. (2005), CO2-H2O mixtures in the geological sequestration of CO2, II Partitioning in chloride brines at 12-100° and up to 600 bar, Geochim. Cosmochim. Acta 69

Land use and land cover over Africa have changed substantially over the last sixty years and this change has been proposed to affect monsoon circulation and precipitation. This study examines the uncertainties on the effect of these changes on the African Monsoon system and Sahel precipitation using an ensemble of regional model simulations with different combinations of land surface and cumulus parameterization schemes. Furthermore, the magnitude of the response covers a broad range of values, most of the simulations show a decline in Sahel precipitation due to the expansion of pasture and croplands at the expense of trees and shrubs and an increase in surface air temperature.

The Weather Research and Forecast Model (WRF) version 3.5 has been used in this study to simulate a heavy rainfall event during the Meiyu season that occurred between 1 and 2 July 2014 over the Yangtze River valley (YRV) in China. The WRF model is driven by the National Centers for Environmental Predictions (NCEP) Final (FNL) global tropospheric analysis data, and eight WRF nested experiments using four different microphysics (MP) schemes and two cumulus parameterizations (CP) are conducted to evaluate the effects of these microphysics and cumulus schemes on heavy rainfall predictions over YRV region. The four MPs selected in this study are Lin et al., WRF Single-Moment 3-class scheme (WSM3), WRF Single-Moment 5-class scheme (WSM5) and WRF Single-Moment 6-class scheme (WSM6), and the two CPs are Kain-Fristch (KF) and Betts-Miller-Janjic (BMJ) schemes. Sensitivity studies showed that all MPs coupling with KF and BMJ CP schemes can well capture the major rain belt from the northeast to southwest with three rainfall centers, but largely overestimate the rainfall near the border between Anhui and Hubei provinces along with the Yellow Sea shore, which produce an opposite trend compared to the observations. Large discrepancies are also presented in WRF simulations of heavy rainfall centers regarding their locations and magnitudes. All MPs coupling with KF CP scheme produced the rainfall areas shifting towards east compared to the observations, while all MPs with BMJ CP scheme tend to better predict the rainfall patterns with slightly more fake precipitation centers. Among all the experiments, the BMJ cumulus scheme has superiority in simulating the Meiyu rainfall over the KF scheme, and the WSM5-BMJ combination shows the best predictive skills.

Precipitation is the main input variable for hydrological modelling. Operational precipitation data are usually provided by rain gauges, weather radar and sometimes satellite observations., Precipitation data with very high spatial and temporal resolution is necessary especially for flash flood forecasting in small catchments. Usually these can neither be provided by rain gauge networks nor satellite measurements. However, radar data has not been used widely in operational flood forecasting yet. Modelling results obtained with radar derived precipitation forcing still don't show a better skill than those obtained by using gauge observations. Radar data suffers from a set of errors. The common ones are uncertainties in the Z-R relation, attenuation effects and uncertain vertical profiles of reflectivity. Corrections for any of these errors have been devised but it has also been shown that some corrections just shift the uncertainty from one source to another. Since the 'true' rainfall field cannot be known, true error statistics cannot be calculated. A measure of uncertainty can be obtained by comparing radar (R) and gauge data (G). Recent developments towards radar ensemble generation focus on the generation of relative uncertainty fields. They are based on comparisons of radar data with gauge data or of radar fields with reference fields obtained by gauge adjustment. The generated fields are then multiplied with the radar field to create the realizations. The proposed approach aims at stochastic simulation of precipitation fields conditioned on radar data In addition, the approach incorporates the additional information available from gauge measurements similarly to radar gauge adjustment. If radar data is adjusted by gauge data using either a multiplicative or an additive correction term, this single correction term can produce unrealistic results when it is regionalized to the radar cells surrounding the reference gauge. This problem can be avoided by splitting

Monolithic bulk metallic glasses (BMGs) exhibit a unique combination of mechanical properties, such as high strength and large elasticity limits, but the lack of ductility is considered the main Achilles' heel of BMG systems. To increase the competitiveness of BMGs vis-à-vis conventional structural materials, the problem of catastrophic failure via intense plastic strain localization (‘shear banding’) has to be addressed. Recent experimental observations suggest that the addition of structural heterogeneities, in the form of crystalline particles, to BMG systems hinders the catastrophic propagation of shear bands and leads to enhanced ductility. These structural heterogeneities can be introduced by either forming BMG composites, where second-phase crystalline particles accommodate applied loads via martensitic transformation mechanisms, or developing glassy alloys that precipitate crystalline particles under deformation, a process by which further deformation can be sustained by twinning mechanisms in the crystalline phase. In this work, we present a non-linear continuum model capable of capturing the structural heterogeneity in the glassy phase and accounting for intrinsic work hardening via martensitic transformations in second-phase reinforcements in BMG composites and deformation twinning in precipitated crystalline particles. Simulation results reveal that in addition to intrinsic work hardening in the crystalline phase, particle size greatly affects the overall mechanical behavior of these BMG systems. The precipitation of crystalline particles in monolithic BMGs yields two-phase microstructures that promote more homogeneous deformation, delay the propagation of incipient shear bands, and ultimately result in improved ductility characteristics.

The successful modelling of the observed precipitation, a very important variable for a wide range of climate applications, continues to be one of the major challenges that climate scientists face today. When the Weather Research and Forecasting (WRF) model is used to dynamically downscale the Climate Forecast System Reanalysis (CFSR) over the Indo-Pacific region, with analysis (grid-point) nudging, it is found that the cumulus scheme used, Betts-Miller-Janjić (BMJ), produces excessive rainfall suggesting that it has to be modified for this region. Experimentation has shown that the cumulus precipitation is not very sensitive to changes in the cloud efficiency but varies greatly in response to modifications of the temperature and humidity reference profiles. A new version of the scheme, denoted "modified BMJ" scheme, where the humidity reference profile is more moist, was developed. In tropical belt simulations it was found to give a better estimate of the observed precipitation as given by the Tropical Rainfall Measuring Mission (TRMM) 3B42 data set than the default BMJ scheme for the whole tropics and both monsoon seasons. In fact, in some regions the model even outperforms CFSR. The advantage of modifying the BMJ scheme to produce better rainfall estimates lies in the final dynamical consistency of the rainfall with other dynamical and thermodynamical variables of the atmosphere.

Calcium carbonate is a major secondary mineral precipitate that influences PRB reactivity and hydraulic performance. In this study, we conducted column experiments to investigate electrical signatures resulting from concurrent CaCO3 and iron oxides precipitation in two simulated PRB media. Solid phase analysis identified CaCO3 (calcite and aragonite) as a major mineral phase throughout the columns, with magnetite being another major phase present close to the influent. Electrical measurements revealed a consistent decrease in conductivity and polarization magnitude of both columns, suggesting that the electrically insulating CaCO3 dominates the electrical response despite the presence of both electrically conductive iron oxides and CaCO3 precipitates. SEM/EDX imaging suggests that the electrical properties result from the geometrical arrangement of the mineral phases. The CaCO3 forms an insulating film on ZVI/magnetite surfaces, which we assume restricts redox-driven transfer of electric charge between the pore electrolyte and ZVI particles, as well as across interconnected ZVI particles. As surface reactivity also depends on the ability of the surface to engage in redox reactions, electrical measurements may provide a minimally invasive technology for monitoring reactivity loss.

A numerical model designed for the study of mesoscale weather phenomena is presented. It is a three-dimensional, time-dependent model based upon a mesoscale primitive-equation system, and it includes parameterizations of cloud and precipitation processes, boundary-layer transfers, and ground surface energy and moisture budgets. This model was used to simulate the lake-effect convergence over and in the lee of Lake Michigan in late fall and early winter. The lake-effect convergence is created in advected cold air as it moves first from cold land to the warm constant-temperature lake surface, and then on to cold land. A numerical experiment with a prevailing northwesterly wind is conducted for a period of twelve hours. Two local maxima of the total precipitation are observed along the eastern shore of Lake Michigan. The results in this hypothetical case correspond quite well to the observed precipitation produced by a real event in which the hypothetical conditions are approximately fulfilled.

Organized deep convection over the North American monsoon region (NAM) is a salient climatic feature that has been the subject of several experimental campaigns and modeling efforts. Recently, however, in Mexico and the Caribbean, there has been mounting interest towards implementing low-cost, low-maintenance GPS-meteorological networks (TLALOCNet and COCOnet) that provide near real-time Integrated Precipitable Water data (IPW) into the assimilation cycle of regional models. A wealth of interesting new observational results concerning the link between the diurnal cycle of deep convection and the processes that could alter it at the surface and aloft has open up opportunities of model verification and improvements to the physics that are specific to subtropical deep convection. In this work, the diurnal cycle of IPW is studied using observational data collected during the North American Monsoon GPS Transect Experiment 2013 experiment and numerical simulations with the Weather Research and Forecasting model (WRF). WRF was run in climate mode to generate a simulation for the entire experiment using ECMWF ERA-Interim analysis data for initial and boundary conditions and spectral nudging. We classified the days during the experiment, according to type of mesoscale phenomena present each day and averaged days with same weather types in both data sets (observed and simulated). Preliminary results show that the simulated diurnal cycle of IPW is very sensitive to Land Use/Land Cover data and to initial and the boundary conditions. Preliminary results show that the simulated amplitude and phase of the diurnal cycle of IPW is well represented only when a more up-to-date LULC is used (MODIS v.s. 99 USGS LULC) and the Thompson mycrophysics scheme is used. In agreement with the previous results, modeled precipitation time series agree better with observed GPS-meterological station reports during the NAM 2013 experiment.

An investigation of several factors which may contribute to the problem of piloting jet transport aircraft in heavy turbulence was conducted by using a piloted simulator that included the most significant airplane response and cockpit vibrations induced by rough air. Results indicated that the primary fuselage structural frequency contributed significantly to a distracting cockpit environment, and there was obtained evidence of severely reduced instrument flight proficiency during simulated maneuvering flight in heavy turbulence. It is concluded that the addition of similar rough-air response capabilities to training simulators would be of value in pilot indoctrination in turbulent-flight procedures.

In the context of the European Cloud Systems project, the problem of the simulation of the diurnal cycle of convective precipitation over land is addressed with the aid of cloud-resolving (CRM) and single-column (SCM) model simulations of an idealized midlatitude case for which observations of large-scale and surface forcing are available. The CRM results are compared to different versions of the European Centre for Medium-Range Weather Forecasts (ECMWF) convection schemes using different convective trigger procedures and convective closures. In the CRM, maximum rainfall intensity occurs at 15 h (local time). In this idealized midlatitude case, most schemes do not reproduce the afternoon precipitation peak, as (i) they cannot reproduce the gradual growth (typically over 3 hours) of the deep convective cloud layer and (ii) they produce a diurnal cycle of precipitation that is in phase with the diurnal cycle of the convective available potential energy (CAPE) and the convective inhibition (CIN), consistent with the parcel theory and CAPE closure used in the bulk mass-flux scheme. The scheme that links the triggering to the large-scale vertical velocity gets the maximum precipitation at the right time, but this may be artificial as the vertical velocity is enforced in the single-column context. The study is then extended to the global scale using ensembles of 72-hour global forecasts at resolution T511 (40 km), and long-range single 40-day forecasts at resolution T159 (125 km) with the ECMWF general-circulation model. The focus is on tropical South America and Africa where the diurnal cycle is most pronounced. The forecasts are evaluated against analyses and observed radiosonde data, as well as observed surface and satellite-derived rainfall rates. The ECMWF model version with improved convective trigger produces the smallest biases overall. It also shifts the rainfall maximum to 12 h compared to 9.5 h in the original version. In contrast to the SCM, the vertical

Bias-correction methods applied to monthly temperature and precipitation data simulated by multiple General Circulation Models (GCMs) are evaluated in this study. Although various methods have been proposed recently, an intercomparison among them using multiple GCM simulations has seldom been reported. Here, five previous methods as well as a proposed new method are compared. Before the comparison, we classified previous methods. The methods proposed in previous studies can be classified into four types based on the following two criteria: 1) Whether the statistics (e.g. mean, standard deviation, or the coefficient of variation) of future simulation is used in bias-correction; and 2) whether the estimation of cumulative probability is included in bias-correction. The methods which require future statistics will depend on the data in the projection period, while those which do not use future statistics are not. The classification proposed can characterize each bias-correction method. These methods are applied to temperature and precipitationsimulated from 12 GCMs in the Coupled Model Intercomparison Project (CMIP3) archives. Parameters of each method are calibrated by using 1948-1972 observed data and validated for the 1974-1998 period. These methods are then applied to GCM future simulations (2073-2097), and the bias-corrected data are intercompared. For the historical simulation, negligible difference can be found between observed and bias-corrected data. However, the difference in the future simulation is large dependent on the characteristics of each method. The frequency (probability) that the 2073-2097 bias-corrected data exceed the 95th percentile of the 1948-1972 observed data is estimated in order to evaluate the differences among methods. The difference between proposed and one of the previous method is more than 10% in many areas. The differences of bias-corrected data among methods are discussed based on their respective characteristics. The results

This study assesses the skill of advanced regional climate models (RCMs) in simulating southeastern United States (SE US) summer precipitation and explores the physical mechanisms responsible for the simulation skill at a process level. Analysis of the RCM output for the North American Regional Climate Change Assessment Program indicates that the RCM simulations of summer precipitation show the largest biases and a remarkable spread over the SE US compared to other regions in the contiguous US. The causes of such a spread are investigated by performing simulations using the Weather Research and Forecasting (WRF) model, a next-generation RCM developed by the US National Center for Atmospheric Research. The results show that the simulated biases in SE US summer precipitation are due mainly to the misrepresentation of the modeled North Atlantic subtropical high (NASH) western ridge. In the WRF simulations, the NASH western ridge shifts 7° northwestward when compared to that in the reanalysis ensemble, leading to a dry bias in the simulated summer precipitation according to the relationship between the NASH western ridge and summer precipitation over the southeast. Experiments utilizing the four dimensional data assimilation technique further suggest that the improved representation of the circulation patterns (i.e., wind fields) associated with the NASH western ridge substantially reduces the bias in the simulated SE US summer precipitation. Our analysis of circulation dynamics indicates that the NASH western ridge in the WRF simulations is significantly influenced by the simulated planetary boundary layer (PBL) processes over the Gulf of Mexico. Specifically, a decrease (increase) in the simulated PBL height tends to stabilize (destabilize) the lower troposphere over the Gulf of Mexico, and thus inhibits (favors) the onset and/or development of convection. Such changes in tropical convection induce a tropical-extratropical teleconnection pattern, which modulates the

coupled and uncoupled models capture the observed signal of the ENSO and MJO oscillations, although with reversed phase in some cases. The austral summer and winter composites of interannual and intraseasonal anomalies showed for wet and dry extreme events the same spatial distribution in models and reanalyses. The interannual variability analysis showed that coupled simulations intensify the impact of the El Niño Southern Oscillation (ENSO) in the Amazon. In the Intraseasonal scale, although the simulations intensify this signal, the coupled models present larger similarities with observations than the atmospheric models for the extremes of precipitation. Note that there are differences between simulated and observed IS anomalies indicating that the models have problems to correctly represent the intensity of low frequency phenomena in this scale. The simulation of ENSO in GCMs can be attributed to their high resolution, mainly in the oceanic component, which contributes to the better solution of the small scale vortices in the ocean. This implies in improvements in the forecasting of sea surface temperature (SST) and as consequence in the ability of atmosphere to respond to this feature.

This paper examines sensitivity of regional climate simulations to spatial resolution using a 20-year simulation of the western U.S. at 40 km resolution and two 5-year simulations at 13 km resolution for the Pacific Northwest and California. The regional climate simulation at 40 km resolution shows a lack of precipitation along coastal hills, good agreements with observations on the windward slopes of the Cascades and Sierra, but over-prediction on the leeside and the basins beyond. Snowpack is grossly under-predicted throughout the western U.S. when compared against observations at snotel sites, which are typically located at the higher altitudes. Comparisons of the 40 km and 13 km resolution simulations suggest that during winter, higher spatial resolution mainly improves the simulation of precipitation in the coastal hills and basins. Along the Cascades and the Sierra Range, however, precipitation is strongly amplified at the higher spatial resolution and compares less favorably with observations. Higher resolution generally improves the spatial distribution of precipitation to yield higher spatial correlation when comparing the simulations to observation. During summer, higher resolution improves not only spatial distribution but also regional mean precipitation.

The increased horizontal resolution of climate models aims to improve the simulations accuracy and to understand the non-linear processes during interactions between different spatial scales within the climate system. Up to this moment, these interactions did not have a good representation on low horizontal resolution GCMs. The variations of extreme climatic events had been described and analyzed in the scientific literature. In a scenario of global warming it is necessary understanding and explaining extreme events and to know if global models may represent these events. The purpose of this study was to understand the impact of the horizontal resolution in high resolution coupled and atmospheric global models of HiGEM project in simulating atmospheric patterns and processes of interaction between spatial scales. Moreover, evaluate the performance of coupled and uncoupled versions of the High-Resolution Global Environmental Model in capturing the signal of interannual and intraseasonal variability of precipitation over Amazon region. The results indicated that the grid refinement and ocean-atmosphere coupling contributes to a better representation of seasonal patterns, both precipitation and temperature, on the Amazon region. Besides, the climatic models analyzed represent better than other models (regional and global) the climatic characteristics of this region. This indicates a breakthrough in the development of high resolution climate models. Both coupled and uncoupled models capture the observed signal of the ENSO and MJO oscillations, although with reversed phase in some cases. The interannual variability analysis showed that coupled simulations intensify the impact of the ENSO in the Amazon. In the intraseasonal scale, although the simulations intensify this signal, the coupled models present larger similarities with observations than the atmospheric models for the extremes of precipitation. The simulation of ENSO in GCMs can be attributed to their high

The dispersion of heavy ion deposited energy is explored in nanometric electronic devices. Experimental data are reported, in a large thin SOI diode and in a SOI FinFET device, showing larger distributions of collected charge in the nanometric volume device. Geant4 simulations are then presented, using two different modeling approaches. Both of them seem suitable to evaluate the dispersion of deposited energy induced by heavy ion beams in advanced electronic devices with nanometric dimensions.

There are several important research questions that the Global Energy and Water Cycle Experiment (GEWEX) is actively pursuing, namely: What is the intensity of the water cycle and how does it change? And what is the sustainability of water resources? Much of the research to address these questions is directed at understanding the atmospheric water cycle. In this paper, we have used a new diagnostic tool, called Water Vapor Tracers (WVTs), to quantify the how much precipitation originated as continental or oceanic evaporation. This shows how long water can remain in the atmosphere and how far it can travel. The model-simulated data are analyzed over regions of interest to the GEWEX community, specifically, their Continental Scale Experiments (CSEs) that are in place in the United States, Europe, Asia, Brazil, Africa and Canada. The paper presents quantitative data on how much each continent and ocean on Earth supplies water for each CSE. Furthermore, the analysis also shows the seasonal variation of the water sources. For example, in the United States, summertime precipitation is dominated by continental (land surface) sources of water, while wintertime precipitation is dominated by the Pacific Ocean sources of water. We also analyze the residence time of water in the atmosphere. The new diagnostic shows a longer residence time for water (9.2 days) than more traditional estimates (7.5 days). We emphasize that the results are based on model simulations and they depend on the model s veracity. However, there are many potential uses for the new diagnostic tool in understanding weather processes and large and small scales.

The fifth-generation PSU NCAR Mesoscale Model (MM5)-based regional climate model (CMM5) capability in simulating the U.S. precipitation annual cycle is evaluated with a 1982 2002 continuous baseline integration driven by the NCEP DOE second Atmospheric Model Intercomparison Project (AMIP II) reanalysis. The causes for major model biases (differences from observations) are studied through supplementary seasonal sensitivity experiments with various driving lateral boundary conditions (LBCs) and physics representations. It is demonstrated that the CMM5 has a pronounced rainfall downscaling skill, producing more realistic regional details and overall smaller biases than the driving global reanalysis. The precipitationsimulation is most skillful in the Northwest, where orographic forcing dominates throughout the year; in the Midwest, where mesoscale convective complexes prevail in summer; and in the central Great Plains, where nocturnal low-level jet and rainfall peaks occur in summer. The actual model skill, however, is masked by existing large LBC uncertainties over data-poor areas, especially over oceans. For example, winter dry biases in the Gulf States likely result from LBC errors in the south and east buffer zones. On the other hand, several important regional biases are identified with model physics deficiencies. In particular, summer dry biases in the North American monsoon region and along the east coast of the United States can be largely rectified by replacing the Grell with the Kain Fritsch cumulus scheme. The latter scheme, however, yields excessive rainfall in the Atlantic Ocean but large deficits over the Midwest. The fall dry biases over the lower Mississippi River basin, common to all existing global and regional models, remain unexplained and the search for their responsible physical mechanisms will be challenging. In addition, the representation of cloud radiation interaction is essential in determining the precipitation distribution and regional

This study evaluates the performances of seven single-column models (SCMs) by comparing simulated surface precipitation with observations at the Atmospheric Radiation Measurement Program Southern Great Plains (SGP) site from January 1999 to December 2001. Results show that although most SCMs can reproduce the observed precipitation reasonably well, there are significant and interesting differences in their details. In the cold season, the model-observation differences in the frequency and mean intensity of rain events tend to compensate each other for most SCMs. In the warm season, most SCMs produce more rain events in daytime than in nighttime, whereas the observations have more rain events in nighttime. The mean intensities of rain events in these SCMs are much stronger in daytime, but weaker in nighttime, than the observations. The higher frequency of rain events during warm-season daytime in most SCMs is related to the fact that most SCMs produce a spurious precipitation peak around the regime of weak vertical motions but rich in moisture content. The models also show distinct biases between nighttime and daytime in simulating significant rain events. In nighttime, all the SCMs have a lower frequency of moderate-to-strong rain events than the observations for both seasons. In daytime, most SCMs have a higher frequency of moderate-to-strong rain events than the observations, especially in the warm season. Further analysis reveals distinct meteorological backgrounds for large underestimation and overestimation events. The former occur in the strong ascending regimes with negative low-level horizontal heat and moisture advection, whereas the latter occur in the weak or moderate ascending regimes with positive low-level horizontal heat and moisture advection.

Numerical simulation experiments were conducted to delineate the influence of in situ deforestation data on episodic rainfall by comparing two ensembles of five 5-day integrations performed with a recent version of the Goddard Laboratory for Atmospheres GCM that has a simple biosphere model (SiB). The first set, called control cases, used the standard SiB vegetation cover (comprising 12 biomes) and assumed a fully forested Amazonia, while the second set, called deforestation cases, distinguished the partially deforested regions of Amazonia as savanna. Except for this difference, all other initial and prescribed boundary conditions were kept identical in both sets of integrations. The differential analyses of these five cases show the following local effects of deforestation. (1) A discernible decrease in evapotranspiration of about 0.80 mm d{sup {minus}1} (roughly 18%) that is quite robust in the averages for 1-, 2-, and 5-day forecasts. (2) A decrease in precipitation of about 1.18 mm d{sup {minus}1} (roughly 8%) that begins to emerge even in 1-2-day averages and exhibits complex evolution that extends downstream with the winds. A larger decrease in precipitation as compared to evapotranspiration produces some drying and warming. The precipitation differences are consistent with the decrease in atmospheric moisture flux convergence and are consistent with earlier simulation studies of local climate change due to large-scale deforestation. (3) A significant decrease in the surface drag force (as a consequence of reduced surface roughness of deforested regions) that, in turn, affects the dynamical structure of moisture convergence and circulation. The surface winds increase significantly during the first day, and thereafter the increase is well maintained even in the 2- and 5-day averages. 34 refs., 9 figs., 2 tabs.

This study assesses the skill of advanced regional climate models (RCMs) in simulating Southeastern United States (SE US) summer precipitation and explores the mechanisms responsible for the simulation skill at a process level. Analysis of the RCM output for the North American Regional Climate Change Assessment Program (NARCCAP) indicates that the RCM simulations of summer precipitation show large biases and a remarkable spread over the SE US. The causes of such a spread are investigated by performing simulations using the Weather Research and Forecasting (WRF) model, a next-generation RCM developed by the US National Center for Atmospheric Research. The results show that the simulated biases in SE US summer precipitation are due mainly to the misrepresentation of the modeled North Atlantic Subtropical High (NASH) western ridge. In WRF simulations, the NASH western ridge shifts 7-deg northwestward compared to that in the reanalysis ensemble, leading to a dry bias in the simulatedprecipitation according to the "NASH western ridge - Southeast summer precipitation" relationship. Experiments utilizing the Four Dimensional Data Assimilation technique further suggest that the improved representation of the circulation patterns associated with the NASH western ridge substantially reduces the bias in simulating SE US summer precipitation. Our analysis of circulation dynamics indicates that the NASH western ridge in the WRF simulations is significantly influenced by planetary boundary layer (PBL) processes over the Gulf of Mexico. Specifically, a decrease (increase) in the simulated PBL height tends to stabilize (destabilize) the lower troposphere over the Gulf of Mexico, and thus inhibits (favors) the onset and/or development of convection. The changes in tropical convecton induce a tropical-extratropical teleconnection pattern, which modulates the circulation along the NASH western ridge in the WRF simulations and contributes to the precipitation biases over the SE US

Convectively forced gravity waves can affect the dynamics of the upper troposphere and middle atmosphere on local to global scales. Simulating these waves requires cloud-resolving models, which are computationally expensive and therefore limited to case studies. Furthermore, full-physics models cannot accurately reproduce the locations, timing, and intensity of individual convective rain cells, limiting the validation of simulated waves. Here, we present a new modeling approach that retains the spatial scope of larger-scale models but permits direct validation of the modeled waves with individual cases of observed waves. Full-physics cloud-resolving model simulations are used to develop an algorithm for converting instantaneous radar precipitation rates over the U.S. into a high-resolution latent heating/cooling field. This heating field is used to force an idealized dry version of the WRF model. Wave patterns and amplitudes observed in individual satellite overpasses are reproduced with remarkable quantitative agreement. The relative simplicity of the new model permits longer simulations with much larger and deeper domains needed to simulate wave horizontal/vertical propagation. Eliminating the complicating factors of cloud physics and radiation this approach provides a link between conceptual and full-physics models and is suitable for studying wave-driven far-field circulation patterns.

SummaryA statistical bias correction methodology for global climate simulations is developed and applied to daily land precipitation and mean, minimum and maximum daily land temperatures. The bias correction is based on a fitted histogram equalization function. This function is defined daily, as opposed to earlier published versions in which they were derived yearly or seasonally at best, while conserving properties of robustness and eliminating unrealistic jumps at seasonal or monthly transitions. The methodology is tested using the newly available global dataset of observed hydrological forcing data of the last 50 years from the EU project WATCH (WATer and global CHange) and an initial conditions ensemble of simulations performed with the ECHAM5 global climate model for the same period. Bias corrections are derived from 1960 to 1969 observed and simulated data and then applied to 1990-1999 simulations. Results confirm the effectiveness of the methodology for all tested variables. Bias corrections are also derived using three other non-overlapping decades from 1970 to 1999 and all members of the ECHAM5 initial conditions ensemble. A methodology is proposed to use the resulting "ensemble of bias corrections" to quantify the error in simulated scenario projections of components of the hydrological cycle.

We analyse the spatial expression of seasonal climates of the Mediterranean and northern Africa in pre-industrial (piControl) and mid-Holocene (midHolocene, 6 yr BP) simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Modern observations show four distinct precipitation regimes characterized by differences in the seasonal distribution and total amount of precipitation: an equatorial band characterized by a double peak in rainfall, the monsoon zone characterized by summer rainfall, the desert characterized by low seasonality and total precipitation, and the Mediterranean zone characterized by summer drought. Most models correctly simulate the position of the Mediterranean and the equatorial climates in the piControl simulations, but overestimate the extent of monsoon influence and underestimate the extent of desert. However, most models fail to reproduce the amount of precipitation in each zone. Model biases in the simulated magnitude of precipitation are unrelated to whether the models reproduce the correct spatial patterns of each regime. In the midHolocene, the models simulate a reduction in winter rainfall in the equatorial zone, and a northward expansion of the monsoon with a significant increase in summer and autumn rainfall. Precipitation is slightly increased in the desert, mainly in summer and autumn, with northward expansion of the monsoon. Changes in the Mediterranean are small, although there is an increase in spring precipitation consistent with palaeo-observations of increased growing-season rainfall. Comparison with reconstructions shows most models underestimate the mid-Holocene changes in annual precipitation, except in the equatorial zone. Biases in the piControl have only a limited influence on midHolocene anomalies in ocean-atmosphere models; carbon-cycle models show no relationship between piControl bias and midHolocene anomalies. Biases in the prediction of the midHolocene monsoon expansion are unrelated to

Cells use three main ways of generating energy currency to drive metabolism: (i) conversion of adenosine diphosphate (ADP) to adenosine triphosphate (ATP) by the proton motive force through the rotor-stator ATP synthase; (ii) the synthesis of inorganic phosphate˜phosphate bonds via proton (or sodium) pyrophosphate synthase; or (iii) substrate-level phosphorylation through the direct donation from an active phosphoryl donor. A mechanism to produce a pyrophosphate bond as “energy currency” in prebiotic systems is one of the most important considerations for origin of life research. Baltscheffsky (1996) suggests that inorganic pyrophosphate (PO74-; PPi) may have preceded ATP/ADP as an energy storage molecule in earliest life, produced by an H+ pyrophosphatase. Here we test the hypothesis that PPi could be synthesized in inorganic precipitatessimulating hydrothermal chimney structures transected by thermal and/or ionic gradients. Appreciable yields of PPi were obtained via substrate phosphorylation by acetyl phosphate within the iron sulfide/silicate precipitates at temperatures expected for an alkaline hydrothermal system. The formation of PPi only occurred in the solid phase, i.e. when both Pi and the phosphoryl donor were precipitated with Fe-sulfides or Fe-silicates. The amount of Ac-Pi incorporated into the precipitate was a significant factor in the amount of PPi that could form, and phosphate species were more effectively incorporated into the precipitate at higher temperatures (⩾50 to >85 °C). Thus, we expect that the hydrothermal precipitate would be more enriched in phosphate (and especially, Ac-Pi) near the inner margins of a hydrothermal mound where PPi formation would be at a maximum. Iron sulfide and iron silicate precipitates effectively stabilized Ac-Pi and PPi against hydrolysis (relative to hydrolysis in aqueous solution). Thus it is plausible that PPi could accumulate as an energy currency up to useful concentrations for early life in a

SummaryTyphoon Morakot (2009) struck Taiwan during 7-9 August 2009, and brought extreme rainfall up to 2855 mm and the worst damages in the past 50 years. The operational models showed deficiency and serious under-prediction in rainfall amount at real time. This study demonstrates that the Cloud-Resolving Storm Simulator (CReSS), a state-of-the-art, high-resolution model, at a grid size of 3 km and starting as early as 0000 UTC 4 August, can successfully simulate and reproduce the event with high accuracy, including the distribution and timing of heavy rainfall in Taiwan. In the simulation starting at 0000 UTC 6 August, for example, the threat scores for 24-h rainfall for 8 August (with extreme amounts >1450 mm) reach 0.8-0.4 even at thresholds of 100-500 mm. This result is only possible due to small track error and the phase-locking mechanism of the Taiwan topography to heavy rainfall. Furthermore, real-time forecast and hindcast integrations of the CReSS model show that high-quality quantitative precipitation forecasts (QPFs) with peak total amount 67-80% of the true value are also obtained from initial conditions at 0000 UTC 6 August, which is about 2 days prior to the beginning of the heaviest rainfall in southern Taiwan. In these integrations, typhoon track errors in the global model forecasts used as boundary conditions are the major error source that prevent more ideal QPF results before and at 1200 UTC 5 August. When properly configured, it is believed that other similar cloud-resolving models can achieve comparable performance. Thus, the importance of and potential benefits from deterministic high-resolution forecasts is stressed, which may give an extended lead-time when the track error is small. With potentially longer time window for emergency action just prior to extreme rainfall events when it matters the most, such forecasts may ultimately lead to reduced losses in lives and properties.

Multi-decadal high resolution climate change simulations over East Asia are performed using the Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model, RegCM3, nested within the NASA/NCAR global model FvGCM. Two sets of simulations are conducted at 20-km grid spacing for present day and future climate (IPCC A2 scenario). The mean precipitation change during the monsoon season (May to September) over China is analyzed and intercompared between the RegCM and FvGCM. Simulation of the present day precipitation by the RegCM shows a better performance than that of the driving FvGCM in terms of both spatial pattern and amount. The main improvement of the RegCM is the removal of an artificial precipitation center over the eastern edge of the Tibetan Plateau simulated by the FvGCM. The FvGCM simulates a predominant increase of precipitation over the region, whereas the RegCM shows extended areas of decrease. The causes of these differences are investigated and explained in terms of the different topographical forcing on circulation and moisture flux in the two models. We also find that the RegCM-simulated changes are in better agreement with observed precipitation trends over East Asia. It is suggested that high resolution models are needed to better investigate future climate projections over China and East Asia.

Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 2001]. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds NRC [2001]." The aerosol effect on Clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path and the "semi-direct" effect on cloud coverage. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect, is even more complex, especially for mixed-phase convective clouds. In this paper, a cloud-resolving model (CRM) with detailed spectral-bin microphysics was used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: South Florida, Oklahoma and the Central Pacific, In all three cases, rain reaches the ground earlier for the low CCN (clean) case. Rain suppression is also evident in all three cases with high CCN (dirty) case. However, this suppression only occurs during the first hour of the simulations. During the mature stages of the simulations, the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case, to almost no effect in the Florida case, to rain enhancement in the Pacific case. These results show the complexity of aerosol interactions with convection. The model results suggest that evaporative cooling is a key process in determining whether high CCN reduces or enhances precipitation. Stronger evaporative cooling can produce a stronger cold pool and thus stronger low-level convergence through interactions

By using a one-dimensional, electromagnetic particle simulation code with full ion and electron dynamics, we have studied the acceleration of heavy ions by a nonlinear magnetosonic wave in a multi-ion-species plasma. First, we describe the mechanism of heavy ion acceleration by magnetosonic waves. We then investigate this by particle simulations. The simulation plasma contains four ion species: H, He, O, and Fe. The number density of He is taken to be 10% of that of H, and those of O and Fe are much lower. Simulations confirm that, as in a single-ion-species plasma, some of the hydrogens can be accelerated by the longitudinal electric field formed in the wave. Furthermore, they show that magnetosonic waves can accelerate all the particles of all the heavy species (He, O, and Fe) by a different mechanism, i.e., by the transverse electric field. The maximum speeds of the heavy species are about the same, of the order of the wave propagation speed. These are in good agreement with theoretical prediction. These results indicate that, if high-energy ions are produced in the solar corona through these mechanisms, the elemental compositions of these heavy ions can be similar to that of the background plasma, i.e., the corona.

A stream temperature module has been developed for the U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) for simulating maximum- and mean-daily stream temperature. This module provides additional simulation capabilities by coupling PRMS with the U.S. Geological Survey Stream Network Temperature (SNTEMP) model. PRMS is a modular, deterministic, distributed-parameter, physical-process watershed model that simulates watershed response to various combinations of climate and land use. Normal and extreme rainfall and snowmelt can be simulated to evaluate changes in water-balance relations, streamflow regimes, soil-water relations, and ground-water recharge. SNTEMP was developed to help aquatic biologists and engineers predict the effects of flow regime changes on water temperatures. This coupling of PRMS with SNTEMP will allow scientists and watershed managers to evaluate the effects of historical climate and projected climate change, landscape evolution, and resource management scenarios on watershed hydrology and in-stream water temperature. The prototype of this coupled model was developed for the U.S. Geological Survey Southeast Regional Assessment Project (SERAP) and tested in the Apalachicola-Chattahoochee-Flint River Basin in the southeastern United States. Preliminary results from the prototype are presented.

Swift heavy ions induce a high density of electronic excitations that can cause the formation of amorphous ion tracks in insulators. No ion tracks have been observed in the semiconductor SiC, but recent experimental work suggests that irradiation damaged SiC can undergo defect recovery under swift heavy ion irradiation. It is believed that local heating of the lattice due to the electronic energy deposition can anneal, and thereby recover, some of the disordered structure. We simulate the local heating due to the ions by the inelastic thermal spike model and perform molecular dynamics simulations of dierent model damage states to study the defect recovery on an atomistic level. We find significant recovery of point defects and a disordered layer, as well as recrystallization at the amorphous-to-crystalline interface of an amorphous layer. The simulation results support the swift heavy ion annealing hypothesis.Swift heavy ions induce a high density of electronic excitations that can cause the formation of amorphous ion tracks in insulators. No ion tracks have been observed in the semiconductor SiC, but recent experimental work suggests that irradiation damaged SiC can undergo defect recovery under swift heavy ion irradiation. It is believed that local heating of the lattice due to the electronic energy deposition can anneal, and thereby recover, some of the disordered structure. We simulate the local heating due to the ions by the inelastic thermal spike model and perform molecular dynamics simulations of dierent model damage states to study the defect recovery on an atomistic level. We find significant recovery of point defects and a disordered layer, as well as recrystallization at the amorphous-to-crystalline interface of an amorphous layer. The simulation results support the swift heavy ion annealing hypothesis.

Bulk quantities of nuclear matter exist only in the compact bodies of the universe. There the crushing gravitational forces overcome the Coulomb repulsion in massive stellar collapses. Nuclear matter is subjected to high pressures and temperatures as shock waves propagate and burn their way through stellar cores. The bulk properties of nuclear matter are important parameters in the evolution of these collapses, some of which lead to nucleosynthesis. The nucleus is rich in physical phenomena. Above the Coulomb barrier, complex interactions lead to the distortion of, and as collision energies increase, the destruction of the nuclear volume. Of critical importance to the understanding of these events is an understanding of the aggregate microscopic processes which govern them. In an effort to understand relativistic heavy-ion reactions, the Boltzmann-Uehling-Uhlenbeck (Ueh33) (BUU) transport equation is used as the framework for a numerical model. In the years since its introduction, the numerical model has been instrumental in providing a coherent, microscopic, physical description of these complex, highly non-linear events. This treatise describes the background leading to the creation of our numerical model of the BUU transport equation, details of its numerical implementation, its application to the study of relativistic heavy-ion collisions, and some of the experimental observables used to compare calculated results to empirical results. The formalism evolves the one-body Wigner phase-space distribution of nucleons in time under the influence of a single-particle nuclear mean field interaction and a collision source term. This is essentially the familiar Boltzmann transport equation whose source term has been modified to address the Pauli exclusion principle. Two elements of the model allow extrapolation from the study of nuclear collisions to bulk quantities of nuclear matter: the modification of nucleon scattering cross sections in nuclear matter, and the

Tune depression in a compact beam equipment is estimated, and numerical simulation results are compared with an experimental one for the compact beam simulator in a driver of heavy ion inertial fusion. The numerical simulation with multi-particle tracking is carried out, corresponding to the experimental condition, and the result is discussed with the experimental one. It is expected that the numerical simulation developed in this paper is useful tool to investigate the beam dynamics in the experiment with the compact beam simulator.

In the framework of the EURO-CORDEX initiative an ensemble of European-wide high-resolution regional climate simulations on a 0.11° ({˜}12.5 km) grid has been generated. This study investigates whether the fine-gridded regional climate models are found to add value to the simulated mean and extreme daily and sub-daily precipitation compared to their coarser-gridded 0.44° ({˜}50 km) counterparts. Therefore, pairs of fine- and coarse-gridded simulations of eight reanalysis-driven models are compared to fine-gridded observations in the Alps, Germany, Sweden, Norway, France, the Carpathians, and Spain. A clear result is that the 0.11° simulations are found to better reproduce mean and extreme precipitation for almost all regions and seasons, even on the scale of the coarser-gridded simulations (50 km). This is primarily caused by the improved representation of orography in the 0.11° simulations and therefore largest improvements can be found in regions with substantial orographic features. Improvements in reproducing precipitation in the summer season appear also due to the fact that in the fine-gridded simulations the larger scales of convection are captured by the resolved-scale dynamics . The 0.11° simulations reduce biases in large areas of the investigated regions, have an improved representation of spatial precipitation patterns, and precipitation distributions are improved for daily and in particular for 3 hourly precipitation sums in Switzerland. When the evaluation is conducted on the fine (12.5 km) grid, the added value of the 0.11° models becomes even more obvious.

Microcosms were treated for a 30-month period with simulatedprecipitation acidified to four pH levels (5.7, 4.5, 4.0, and 3.5) to evaluate the impact of acid precipitation on foliar leaching, plant nutrient content, soil leaching, soil nutrient content, and litter decomposition. Direct effects of acid precipitation on diameter growth, bud break, leaf senescence, chlorophyll content, stomatal size, stomatal density, photosynthesis, respiration, transpiration, and cuticle erosion were evaluated on tulip poplar, white oak, and Virginia pine seedlings growing as mixed stands in the microcosms. None of the plant physiological or morphological parameters evaluated responded in a statistically significant manner as a result of treatment. A significant treatment canopy interaction was observed in the form of a 60 percent increase in calcium input in throughfall in response to the pH 3.5 treatment. Foliar nutrient content did not change in response to treatment nor did field measurements of decomposer activity. Soil analysis indicated a significantly lower concentration of exchangeable calcium and magnesium in the top 3.5 cm of the mineral soil in association with the pH 3.5 treatment. Soil leachate concentrations exhibited significant increases at both the 25 and 50 cm depths. However, at the 100 cm depth no significant response in concentration or elemental loss from the system was observed. Laboratory respiration measurements indicated a small, but statistically significant reduction in decomposer activity in the lower litter (02) horizon. This reduction was masked in the field measurements of decomposer activity due to the relatively small contribution of the 02 to total soil respiration. 38 references, 12 figures, 18 tables.

Numerical simulations of precipitation depend to a large degree on the assumed cloud microphysics schemes representing the formation, growth and fallout of cloud droplets and ice crystals. Recent studies show that assumed cloud microphysics play a major role not only in forecasting precipitation, especially in cases of extreme precipitation events, but also in the quality of the passive microwave rainfall estimation. Evaluations of the various Weather Research Forecasting (WRF) model microphysics schemes in this study are based on a method that was originally developed to construct the a-priori databases of precipitation profiles and associated brightness temperatures (TBs) for precipitation retrievals. This methodology generates three-dimensional (3D) precipitation fields by matching the GPM dual frequency radar (DPR) reflectivity profiles with those calculated from cloud resolving model (CRM)-derived hydrometeor profiles. The method eventually provides 3D simulatedprecipitation fields over the DPR scan swaths. That is, atmospheric and hydrometeor profiles can be generated at each DPR pixel based on CRM and DPR reflectivity profiles. The generated raining systems over DPR observation fields can be applied to any radiometers that are unaccompanied with a radar for microwave radiative calculation with consideration of each sensor's channel and field of view. Assessment of the WRF model microphysics schemes for several typhoon cases in terms of emission and scattering signals of GMI will be discussed.

We describe how the Climate Corporation uses Python and Clojure, a language impleneted on top of Java, to generate climatological forecasts for precipitation based on the Advanced Hydrologic Prediction Service (AHPS) radar based daily precipitation measurements. A 2-year-long forecasts is generated on each of the ~650,000 CONUS land based 4-km AHPS grids by constructing 10,000 ensembles sampled from a 30-year reconstructed AHPS history for each grid. The spatial and temporal correlations between neighboring AHPS grids and the sampling of the analogues are handled by Python. The parallelization for all the 650,000 CONUS stations is further achieved by utilizing the MAP-REDUCE framework (http://code.google.com/edu/parallel/mapreduce-tutorial.html). Each full scale computational run requires hundreds of nodes with up to 8 processors each on the Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) distributed computing service resulting in 3 terabyte datasets. We further describe how we have productionalized a monthly run of the simulations process at full scale of the 4km AHPS grids and how the resultant terabyte sized datasets are handled.

A mathematical model (FPM) is presented to predict the transformation of heavy metals in the downstream of combustor or incinerator. The model accounts for the transformation of heavy metals through the combined effect of condensation, nucleation, coagulation, external force and thermophoresis force. The calculation of heavy metals is embodied in the post-processor appended to Fluent software. Before the simulation, velocity, temperature, PbCl{sub 2} concentration and other initial parameters are obtained by experiment. In addition, the transformation of PbCl{sub 2} is also experimentally studied. The comparison of experimental and predicted results indicate that the fine particle model (FPM) is valid for predicting the transformation of heavy metals in the downstream of incinerator or combustor.

A mathematical model (FPM) is presented to predict the transformation of heavy metals in the downstream of combustor or incinerator. The model accounts for the transformation of heavy metals through the combined effect of condensation, nucleation, coagulation, external force and thermophoresis force. The calculation of heavy metals is embodied in the post-processor appended to Fluent soft. Before the simulation, velocity, temperature, PbCl2 concentration and other initial parameters are obtained by experiment. In addition, the transformation of PbCl2 is also experimentally studied. The comparison of experimental and predicted results indicate that the fine particle model (FPM) is valid for predicting the transformation of heavy metals in the downstream of incinerator or combustor. PMID:17182393

Climate data homogenisation is of major importance in monitoring climate change, the validation of weather forecasting, general circulation and regional atmospheric models, modelling of erosion, drought monitoring, among other studies of hydrological and environmental impacts. This happens because non-climate factors can cause time series discontinuities which may hide the true climatic signal and patterns, thus potentially bias the conclusions of those studies. In the last two decades, many methods have been developed to identify and remove these inhomogeneities. One of those is based on geostatistical simulation (DSS - direct sequential simulation), where local probability density functions (pdf) are calculated at candidate monitoring stations, using spatial and temporal neighbouring observations, and then are used for detection of inhomogeneities. This approach has been previously applied to detect inhomogeneities in four precipitation series (wet day count) from a network with 66 monitoring stations located in the southern region of Portugal (1980-2001). This study revealed promising results and the potential advantages of geostatistical techniques for inhomogeneities detection in climate time series. This work extends the case study presented before and investigates the application of the geostatistical stochastic approach to ten precipitation series that were previously classified as inhomogeneous by one of six absolute homogeneity tests (Mann-Kendall test, Wald-Wolfowitz runs test, Von Neumann ratio test, Standard normal homogeneity test (SNHT) for a single break, Pettit test, and Buishand range test). Moreover, a sensibility analysis is implemented to investigate the number of simulated realisations that should be used to accurately infer the local pdfs. Accordingly, the number of simulations per iteration is increased from 50 to 500, which resulted in a more representative local pdf. A set of default and recommended settings is provided, which will help

This study assesses the ability of the Phase 5 Coupled Model Intercomparison Project (CMIP5) simulations in capturing the interdecadal precipitation enhancement over the Yangtze River valley (YRV) and investigates the contributions of Arctic warming to the interdecadal variability of the East Asian summer monsoon rainfall. Six CMIP5 historical simulations including models from Canada (CCCma), China (BCC), Germany (MPI-M), Japan (MRI), United Kingdom (MOHC), and United States (NCAR) are used. The NCEP/NCAR reanalysis and observed precipitation are also used for comparison. Among the six CMIP5 simulations, only CCCma can approximately simulate the enhancement of interdecadal summer precipitation over the YRV in 1990-2005 relative to 1960-1975, and the relationships between the summer precipitation with surface temperature (Ts), the 850hPa winds, and 500hPa height field (H500), and between Ts and H500 using regression, correlation, and SVD analyses. It is found that CCCma can reasonably simulate the interdecadal surface warming over the boreal mid-to high latitudes and the Arctic in winter, spring and summer. The summer Baikal blocking appears to be the bridge that links the winter and spring surface warming over the mid-to high latitude and Arctic with the enhancement of summer precipitation over the YRV. Models that missed some or all of these relationships found in CCCma and the reanalysis failed to simulate the interdecadal enhancement of precipitation over the YRV. This points to the importance of high latitude and Arctic processes on interdecadal variability of the East Asian summer monsoon and the challenge for global climate models to correctly simulate the linkages.

Among weather phenomena, convection, due to its complexity and destructive nature, has been subject of many studies and researches through out the world. For decades, generating different types of models were attempted by scientists to provide possibility of abating or at least reducing convective weather phenomena effects on people's life. People in south and southwest of Iran are familiar with convective phenomena and their effects. Due to Socio-Economic importance of convective phenomena and availability of a meso-scale (MM5) model in Iranian meteorological Organization it has been tried to investigate the model ability to simulate and to predict convective precipitation in south and southwest of the country. Outcome of the study indicates that the model produces acceptable results on convection that arises from sharp baroclinic conditions; but it has failed to produce acceptable results where convection is due to local conditions. Keywords: Convection, Numerical Weather Prediction, MM5 model, Baroclinic

This study evaluates the performance of two bias correction techniques—power transformation and gamma distribution adjustment—for Eta regional climate model (RCM) precipitationsimulations. For the gamma distribution adjustment, the number of dry days is not taken as a fixed parameter; rather, we propose a new methodology for handling dry days. We consider two cases: the first case is defined as having a greater number of simulated dry days than the observed number, and the second case is defined as the opposite. The present climate period was divided into calibration and validation sets. We evaluate the results of the two bias correction techniques using the Kolmogorov-Smirnov nonparametric test and the sum of the differences between the cumulative distribution curves. These tests show that both correction techniques were effective in reducing errors and consequently improving the reliability of the simulations. However, the gamma distribution correction method proved to be more efficient, particularly in reducing the error in the number of dry days.

For conventional fixed wing and rotary wing aircraft a variety of modeling and simulation tools have been developed to provide designers the means to thoroughly investigate proposed designs and operational concepts. However, lighter-than-air (LTA) airships, hybrid air vehicles, and aerostats have some important aspects that are different from heavier-than-air (HTA) vehicles. In order to account for these differences, modifications are required to the standard design tools to fully characterize the LTA vehicle design and performance parameters.. To address these LTA design and operational factors, LTA development organizations have created unique proprietary modeling tools, often at their own expense. An expansion of this limited LTA tool set could be accomplished by leveraging existing modeling and simulation capabilities available in the National laboratories and public research centers. Development of an expanded set of publicly available LTA modeling and simulation tools for LTA developers would mitigate the reliance on proprietary LTA design tools in use today. A set of well researched, open source, high fidelity LTA design modeling and simulation tools would advance LTA vehicle development and also provide the analytical basis for accurate LTA operational cost assessments. This paper will present the modeling and analysis tool capabilities required for LTA vehicle design, analysis of operations, and full life-cycle support. A survey of the tools currently available will be assessed to identify the gaps between their capabilities and the LTA industry's needs. Options for development of new modeling and analysis capabilities to supplement contemporary tools will also be presented.

In order to evaluate the consequences of climate change for agriculture and the economy we need to develop climate models capable of correctly simulating regional precipitation patterns. The deficiency of global climate models in the simulation of orographic precipitation may be related to the crudeness of model topography. Inadequacies in the parameterizations of physical processes cause additional errors in the calculation of orographic as well as frontal precipitation. In this study, we have investigated the role of model resolution in simulating the geographical distribution of precipitation over China. Comparisons are made between observations and the calculated precipitation fields in a seasonal run with climatological sea surface temperatures. This study describes results for June and July from 12 month simulations of the ECMWF model at the following four resolutions: T21 (5{times}5 degree), T42 (3{times}3 degree), T63 (2{times}2 degree) and T106 (1{times}1 degree). A description of this model is given by Simmons et. al. (1988). The various resolutions of the ECMWF model are virtually identical with the exception of the gravity wave drag (Palmer et al. 1986), vertical diffusion coefficients and orography. The T21 resolution lacks gravity wave drag completely.

Climate data homogenisation is of major importance in climate change monitoring, validation of weather forecasting, general circulation and regional atmospheric models, modelling of erosion, drought monitoring, among other studies of hydrological and environmental impacts. The reason is that non-climate factors can cause time series discontinuities which may hide the true climatic signal and patterns, thus potentially bias the conclusions of those studies. In the last two decades, many methods have been developed to identify and remove these inhomogeneities. One of those is based on a geostatistical simulation technique (DSS - direct sequential simulation), where local probability density functions (pdfs) are calculated at candidate monitoring stations using spatial and temporal neighbouring observations, which then are used for the detection of inhomogeneities. Such approach has been previously applied to detect inhomogeneities in four precipitation series (wet day count) from a network with 66 monitoring stations located in the southern region of Portugal (1980-2001). That study revealed promising results and the potential advantages of geostatistical techniques for inhomogeneity detection in climate time series. This work extends the case study presented before and investigates the application of the geostatistical stochastic approach to ten precipitation series that were previously classified as inhomogeneous by one of six absolute homogeneity tests (Mann-Kendall, Wald-Wolfowitz runs, Von Neumann ratio, Pettitt, Buishand range test, and standard normal homogeneity test (SNHT) for a single break). Moreover, a sensitivity analysis is performed to investigate the number of simulated realisations which should be used to infer the local pdfs with more accuracy. Accordingly, the number of simulations per iteration was increased from 50 to 500, which resulted in a more representative local pdf. As in the previous study, the results are compared with those from the

Water is an important resource for plant life. Since climate scenarios for Switzerland predict an average reduction of 20% in summer precipitation until 2070, understanding ecosystem responses to water shortage, e.g. in terms of plant productivity, is of major concern. Thus, we tested the effects of simulated summer drought on three managed grasslands along an altitudinal gradient in Switzerland from 2005 to 2007, representing typical management intensities at the respective altitude. We assessed the effects of experimental drought on above- and below-ground productivity, stand structure (LAI and vegetation height) and resource use (carbon and water). Responses of community above-ground productivity to reduced precipitation input differed among the three sites but scaled positively with total annual precipitation at the sites (R2=0.85). Annual community above-ground biomass productivity was significantly reduced by summer drought at the alpine site receiving the least amount of annual precipitation, while no significant decrease (rather an increase) was observed at the pre-alpine site receiving highest precipitation amounts in all three years. At the lowland site (intermediate precipitation sums), biomass productivity significantly decreased in response to drought only in the third year, after showing increased abundance of a drought tolerant weed species in the second year. No significant change in below-ground biomass productivity was observed at any of the sites in response to simulated summer drought. However, vegetation carbon isotope ratios increased under drought conditions, indicating an increase in water use efficiency. We conclude that there is no general drought response of Swiss grasslands, but that sites with lower annual precipitation seem to be more vulnerable to summer drought than sites with higher annual precipitation, and thus site-specific adaptation of management strategies will be needed, especially in regions with low annual precipitation.

An increase of intense rainfall events in the center regions of Europe is one of the assumed effects of climate change. Climate scenarios indicate also large seasonal and regional differences concerning the magnitude. Structural damages and financial loss resulting from heavyprecipitation depend on natural parameters such as topography and vegetation cover of the specific area, but also on socio-economic parameters such as urbanized and industrialized areas, population density and the presence of critical infrastructure. In particular mudflows and floods cause damages such as flooded basements and streets, undercutting of roads or spilled sewage drains. The emergency management has to consider these effects appropriately. Commonly, this is the responsibilities is taken by the fire brigades and civil protection units. Within their daily routines, numerous data is collected, but commonly not utilized for scientific purposes. In particular fire brigade operation data can be used accordingly to describe the intensity of the aftermath when heavyprecipitation strikes a certain area. One application is described in this study based on a example in Offenbach, Germany. The civil protection in Germany is based on a federal system with a bottom-up command-structure and responsibility to the local community. Therefore it is not easy to collect the overall incident data for a widespread affected area. To examine particular local effects of heavyprecipitation events it is necessary to match the meteorological data provided by the German Meteorological Service (DWD) with the incident data of all effected fire brigades, which sometimes is impeded by the usual resolution of meteorological data. In this study, a method of comprehensive evaluation of meteorological data and the operation data from local fire brigades has been developed for the Rhine-Main-Area. This area is one of the largest metropolitan regions in Germany with a very high density in population as well as

A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulatedprecipitation decrease and forest dieback. Rising atmospheric CO2 is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO2 was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO2 contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO2 and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.

A mathematical model for a two-phase flow laminar airfoil in simulatedheavy rain has been established. The set of non-linear partial differential equations has been converted into a set of finite difference equations; appropriate initial and boundary conditions are provided. The numerical results are compared with the experimental measurements. They show good agreement in quality.

Accurate simulation of extreme weather events remains a challenge in climate models. Previous studies indicate that regional climate models better reproduce extreme precipitation with their higher spatial resolution than coarser resolution global climate models. This study utilized radar-based hourly precipitation data with a resolution of 4 km to evaluate rainfall characteristics simulated with NASA Unified Weather Research and Forecasting (NU-WRF) model at horizontal resolutions of 24, 12 and 4 km. We also examined the impact of spectral nudging on the performance of NU-WRF. The rainfall characteristics in the observations and simulations were defined as a joint probability distribution function (JPDF) between duration and peak intensity of precipitation events over the Great Plains in summer. The Regional Climate Model Evaluation System (RCMES) is an open source software suite developed jointly by NASA's Jet Propulsion Laboratory and the University of California, Los Angeles. RCMES facilitates evaluation of NU-WRF evaluations by providing tools to process a vast amount of observational and model datasets with high resolutions. Using RCMES, we calculated JPDF for each dataset and the overlapping area between observed and simulated JPDFs to measure the similarity between the two JPDFs. The performance of NU-WRF simulations based on the precipitation JPDF is strongly dependent on their resolutions. The simulation with the highest resolution of 4 km shows the best agreement with the observations with the same resolution in simulating short-duration downpour events over the Great Plains. Our analysis indicates that even the regridded high-resolution simulation on low-resolution grids shows better performance than low-resolution simulations. The simulations with lower resolutions of 12 and 24 km show reasonable agreement only with the observational data whose resolutions are similar to the simulations.

Inelastic hadronic interactions in heavy targets have been simulated using Geant4 and compared with experimental data for thin and thick lead and uranium targets. Special attention is paid to neutron and fission fragment production. Good agreement in the description of proton-beam interaction with thick targets is demonstrated, which is important for the simulation of experiments aimed at the development of subcritical reactors.

Many structural transformations result in several orientation variants whose volume fractions and distributions can be controlled by applied stresses during nucleation, growth or coarsening. Depending on the type of stress and the coupling between the applied stress and the lattice misfit strain, the precipitate variants may be aligned parallel or perpendicular to the stress axis. This paper reports their studies on the effect of applied stresses on nucleation and growth of coherent {theta}{prime} precipitates in Al-Cu alloys using computer simulations based on a diffuse-interface phase-field kinetic model. In this model, the orientational differences among precipitate variants are distinguished by non-conserved structural field variables, whereas the compositional difference between the precipitate and matrix is described by a conserved field variable. The temporal evolution of the spatially dependent field variables is determined by numerically solving the time-dependent Ginzburg-Landau (TDGL) equations for the structural variables and the Cahn-Hilliard diffusion equation for composition. Random noises were introduced in both the composition and the structural order parameter fields to simulate the nucleation of {theta}{prime} precipitates. It is demonstrated that although an applied stress affects the microstructural development of a two-phase alloy during both the nucleation and growth stages, it is most effective to apply stresses during the initial nucleation stage for producing anisotropic precipitate alignment.

Bias correction of meteorological variables from climate model simulations is a routine strategy for circumventing known limitations of state-of-the-art general circulation models. Although the assessment of climate change impacts often depends on the joint variability of multiple variables, commonly used bias correction methodologies treat each variable independently and do not consider the relationship among variables. Independent bias correction can therefore produce non-physical corrections and may fail to capture important multivariate relationships. Here, we introduce a joint bias correction methodology (JBC) and apply it to precipitation (P) and temperature (T) fields from the fifth phase of the Climate Model Intercomparison Project (CMIP5) model ensemble. This approach is based on a general bivariate distribution of P-T and can be seen as a multivariate extension of the commonly used univariate quantile mapping method. It proceeds by correcting either P or T first and then correcting the other variable conditional upon the first one, both following the concept of the univariate quantile mapping. JBC is shown to not only reduce biases in the mean and variance of P and T similarly to univariate quantile mapping, but also to correct model-simulated biases in P-T correlation fields. JBC, using methods such as the one presented here, thus represents an important step in impacts-based research as it explicitly accounts for inter-variable relationships as part of the bias correction procedure, thereby improving not only the individual distributions of P and T, but critically, their joint distribution.

One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

Water is an important resource for plant live. Since climate scenarios for Switzerland predict an average reduction of 20% in summer precipitation until 2070, understanding ecosystem responses to water shortage, e.g. in terms of plant productivity, is of major concern. Thus, we tested the effects of simulated summer drought on three managed grasslands along an altitudinal gradient in Switzerland from 2005 to 2007, representing typical management intensities at the respective altitude. We assessed the effects of drought on above- and below-ground productivity, stand structure (LAI and vegetation height) and resource use (carbon and water). Drought responses of community above-ground productivity differed among the three sites but scaled positively with total annual precipitation at the sites (R2=0.85). Annual community above-ground biomass productivity was significantly reduced by summer drought at the alpine site receiving the least amount of annual precipitation, while no significant decrease (rather an increase) was observed at the pre-alpine site receiving highest precipitation amounts in all three years. At the lowland site (intermediate precipitation sums), biomass productivity significantly decreased in response to drought only in the third year, after showing increased abundance of a drought tolerant weed species in the second year. No significant change in below-ground biomass productivity was observed at any of the sites in response to simulated summer drought. However, community carbon isotope ratios increased under drought conditions, indicating an increase in water use efficiency. We conclude that there is no general drought response of Swiss grasslands, but that sites with lower annual precipitation seem to be more vulnerable to summer drought than sites with higher annual precipitation, and thus site-specific adaptation measures will be needed especially in regions with low annual precipitation.

Current climate integrations with the National Center for Atmospheric Research Community Climate Model (CCM3) show a very pronounced dry bias in summer precipitation over the North American Monsoon System (NAMS) region. Additionally, summer precipitation totals in this region show a smaller than observed interannual variability and a weak response to changes in SSTs. To understand the reasons behind the CCM3 misrepresentation of monsoonal processes in the NAMS region, we have chosen to examine model simulation during two extreme years: 1984 (wet) and 1993 (dry). These two years were selected according to observed precipitation totals in the northernmost portion, i.e. Arizona and New Mexico, of the NAMS region. Ensemble AMIP-type simulations with CCM3 in its standard configuration (i.e., at T42 resolution and coupled to its standard land surface model; LSM) show only small differences in precipitation over the NAMS region between the two chosen extreme years. When CCM3 is coupled to BATS and integrated over several years with SSTs for the two contrasting years, the differences in summer precipitation remain much smaller than the observed differences. In a final experiment, CCM3 is coupled to the fine-mesh version of BATS (named HRBATS), which is described in Hahmann and Dickinson (2001). This model allows for explicit representation of sub-grid variations in vegetation and soils and the inclusion of fractional ocean areas. In these simulations, a very pronounced difference in precipitation, comparable to the observed precipitation differences, is seen between the two contrasting years. The possible physical mechanisms that might explain these differences are explored in this talk. Possible reasons include the presence of the waters of the Gulf of California, which might provide a moisture source, and the better representation of snow cover over the prior winter and spring seasons.

The School of Chemistry Environmental Technology Laboratory generates 43.4 1 of effluent with low pH (0.7) and high contents of COD (1908 mgO2 l(-1)), phenol (132.1 mg l(-1)), sulfate (36700 mg l(-1)) and heavy metals (28.2 mg Hg l(-1); 82.1 mg Cr(total) l(-1); 30.8 mg Cu l(-1); 57.4 mg Fe(total) l(-1); 16.2 mg Al l(-1)) weekly. These data show that this effluent presents high toxicity for biological treatment, with a physical-chemical step being necessary before a biological step. Preliminary studies showed that the most toxic constituents of the effluent were sulfate, phenol and total chromium. In this work, a chemical precipitation step with sodium hydroxide or lime was evaluated for the toxicity reduction on anaerobic microbial consortium. These experiments were carried out with increasing concentrations of alkalis in the effluent in order to obtain pH initial values of 8-12. Similar results were obtained for COD (15-28%), turbidity (95-98%), phenol (13-24%) and total chromium (99.8-99.9%) removals in each condition studied with soda or lime. Sulfate was only removed by precipitation with lime, obtaining reductions from 84 to 88%. The toxicity on the anaerobic sludge was studied employing specific methanogenic activity (SMA) analysis of raw and treated effluent (after chemical precipitation step). The SMA experiments showed that chemical precipitation at pH 8 reduces the toxic effect of the effluent on anaerobic microbial consortium three times (with soda) and thirteen times (with lime). These results indicate that precipitation with lime is more efficient at toxicity removal, however the produced sludge volume is around two times higher than that produced with soda. PMID:17285944

This study examines persistent and short-lived heavyprecipitation events (PHPEs and SHPEs, respectively) in South China during summer (July-September) 1975-2009 in association with large-scale circulation and moisture processes at different timescales. Compared to SHPEs, PHPEs are characterized by long-lasting enhanced convection and cyclonic moisture circulation as well as strengthened moisture convergence over South China. Examination of environmental variables at different timescales suggests that intraseasonal and synoptic components play a deterministic role in regulating the overall changes in convection and moisture convergence, while the low-frequency background state plays only a marginal role. Further analysis of the moisture divergence terms also reveals that the overall changes in moisture divergence during PHPEs and SHPEs stem primarily from variations in the intraseasonal and synoptic wind fields rather than in the humidity fields. Overall, it is found that the location and strength of the intraseasonal oscillation (ISO) and the synoptic disturbances play a decisive role in controlling the severity and duration of rainfall events over South China. The synchronization and persistence of the enhanced convection and moisture circulation of the ISO and synoptic disturbances jointly contribute to prolonged heavyprecipitation over South China, while the weakening and asynchrony of the associated convection and moisture circulation at different timescales result in rainfall events of weaker intensity and shorter duration.

Land use and land cover over Africa have changed substantially over the last sixty years and this change has been proposed to affect monsoon circulation and precipitation. This study examines the uncertainties on the effect of these changes on the African Monsoon system and Sahel precipitation using an ensemble of regional model simulations with different combinations of land surface and cumulus parameterization schemes. Furthermore, the magnitude of the response covers a broad range of values, most of the simulations show a decline in Sahel precipitation due to the expansion of pasture and croplands at the expense of trees and shrubsmore » and an increase in surface air temperature.« less

Studies of irradiation effects in inorganic polymers and gels performed at CSNSM during the last ten years are summarized, and new results concerning the effect of the density of transferred energy on the precipitation kinetics of C, Si and metal clusters are presented. The precipitation yield as a function of the fluence of ions with different masses and energies was investigated by means of various spectroscopies, depending on the particles nature. The rates of gel to ceramics conversion and of C, Si and metal precipitation are determined by the density of electronic excitations and nuclear collisions have little effect. Particles formed by ion irradiation show a narrower size distribution and, consequently, more interesting characteristics for magnetic or optical applications than those formed in heat treated gels.

Simulations of spray dispersion in a simplified tractor-trailer wake have been completed with the goal of obtaining a better understanding of how to mitigate this safety hazard. The Generic Conventional Model (GCM) for the tractor-trailer was used. The impact of aerodynamic drag reduction devices, specifically trailer-mounted base flaps, on the transport of spray in the vehicle wake was considered using the GCM. This analysis demonstrated that base flaps including a bottom plate may actually worsen motorist visibility because of the interaction of fine spray with large vortex flows in the wake. This work suggests that to use computational fluid dynamics (CFD) to design and evaluate spray mitigation strategies the jet or sheet breakup processes can be modeled using an array of injectors of small (< 0.1 mm) water droplets; however the choice of size distribution, injection locations, directions and velocities is largely unknown and requires further study. Possible containment strategies would include using flow structures to 'focus' particles into regions away from passing cars or surface treatments to capture small drops.

The impact of the circulation shift under climate warming on the distribution of precipitation extremes and the associated sensitivity to model resolution are investigated using the aquaplanet Community Atmosphere Model CAM3. The response of the probability density function of the precipitation to a uniform SST warming can be interpreted as superimposition of a dynamically induced poleward shift and a thermodynamically induced upward shift toward higher intensities, which give rise to manyfold increase in the frequency of the most extreme categories of the precipitation events at the poleward side of the midlatitude storm track. Meanwhile, the thermodynamic contribution to the intensification of the precipitation extremes is substantially less than expected from the Clausius-Clapeyron relation, implicative of significant change in the vertical structure of the precipitation processes. While coarser resolutions underestimate the dynamical contribution to the increase of precipitation extremes, a modest increase of the equator-to-pole SST warming gradient can have a significant opposite effect.

Precipitation would be one of the major sources of uncertainty for hydrological analysis since precipitation is the main input of the hydrological models, in that sense, is one of the first factors controlling the accuracy of Rainfall Run-off (R-R) modeling. However, sparse meteorological data in un-gauged or poorly gauged basins has been a long concerning issue that bottlenecks the quantification of the hydrological budget. In recent decades, remote sensing techniques with their broad spatial coverage and repeat temporal coverage would grasp well the spatial distribution of precipitation over the river basin. However, remote sensing rainfall estimates are not direct measurements of rainfall that are subjects to variety of error sources and exhibit the limitation for rainfall budget accuracy. Therefore, it is appealing to incorporate the precision of point measurements of the local rainfall stations with the fine spatial distribution of satellite-based rainfall estimates to obtain a good quality of precipitation field in space and time to take the advantages of the both two datasets. The aim of my research is blending the remote sensing satellite precipitation, GsMAP-MVK (Global Satellite Mapping of Precipitation moving vector with Kalman filter) with a very high spatial distribution, with the local rainfall measurements for improvement of quantitative rainfall estimates and run-off predictions capability. Several satellite-gauge merging methods with various complexity degrees: from linear merging, power transformation merging to geo-statistical merging techniques were utilized to provide the precipitation input for conceptual hydrological model HBV for run-off simulation in Da river basin in Vietnam. The Geo-statistical merging methods give the best results for stream-flow simulation. Key Words: Remote sensed satellite data, hydrological model, un-gauged basin, bias correction.

The global fully coupled half-degree Community Climate System Model Version 4 (CCSM4) was integrated for a suite of climate change ensemble simulations including five historical runs, five Representative Concentration Pathway 8.5 [RCP8.5) runs, and a long Pre-Industrial control run. This study focuses on precipitation at regional scales and its sensitivity to horizontal resolution. The half-degree historical CCSM4 simulations are compared to observations, where relevant, and to the standard 1° CCSM4. Both the halfdegree and 1° resolutions are coupled to a nominal 1° ocean. North American and South Asian/Indian monsoon regimes are highlighted because these regimes demonstrate improvements due to highermore » resolution, primarily because of better-resolved topography. Agriculturally sensitive areas are analyzed and include Southwest, Central, and Southeast U.S., Southern Europe, and Australia. Both mean and extreme precipitation is discussed for convective and large-scale precipitation processes. Convective precipitation tends to decrease with increasing resolution and large-scale precipitation tends to increase. Improvements for the half-degree agricultural regions can be found for mean and extreme precipitation in the Southeast U.S., Southern Europe, and Australian regions. Climate change responses differ between the model resolutions for the U.S. Southwest/Central regions and are seasonally dependent in the Southeast and Australian regions. Both resolutions project a clear drying signal across Southern Europe due to increased greenhouse warming. As a result, differences between resolutions tied to the representation of convective and large-scale precipitation play an important role in the character of the climate change and depend on regional influences.« less

Large-eddy simulation is used to study the sensitivity of trade wind cumulus clouds to perturbations in cloud droplet number concentrations. We find that the trade wind cumulus system approaches a radiative-convective equilibrium state, modified by net warming and drying from imposed large-scale advective forcing. The system requires several days to reach equilibrium when cooling rates are specified but much less time, and with less sensitivity to cloud droplet number density, when radiation depends realistically on the vertical distribution of water vapor. The transient behavior and the properties of the near-equilibrium cloud field depend on the microphysical state and therefore on the cloud droplet number density, here taken as a proxy for the ambient aerosol. The primary response of the cloud field to changes in the cloud droplet number density is deepening of the cloud layer. This deepening leads to a decrease in relative humidity and a faster evaporation of small clouds and cloud remnants constituting a negative lifetime effect. In the near-equilibrium regime, the decrease in cloud cover compensates much of the Twomey effect, i.e., the brightening of the clouds, and the overall aerosol effect on the albedo of the organized precipitating cumulus cloud field is small.

Precipitable water vapor (PWV) derived from a numerical weather prediction (NWP) model were compared to observations derived from ground-based Global Positioning System (GPS) receivers. The model data compared were from the Weather Research and Forecasting (WRF) model short-range forecasts on nested grids. The numerical experiments were performed by selecting the cloud microphysics schemes and for the comparisons, the Changma period of 2008 was selected. The observational data were derived from GPS measurements at 9-sites in South Korea over a 1-month period, in the middle of June-July 2008. In general, the WRF model demonstrated considerable skill in reproducing the temporal and spatial evolution of the PWV as depicted by the GPS estimations. The correlation between forecasts and GPS estimates of PWV depreciated slowly with increasing forecast times. Comparing simulations with a resolution of 18 km and 6 km showed no obvious PWV dependence on resolution. Besides, GPS and the model PWV data were found to be in quite good agreement with data derived from radiosondes. These results indicated that the GPS-derived PWV data, with high temporal and spatial resolution, are very useful for meteorological applications.

The large-scale mechanically agitated tank has been widely used in the decomposition process of sodium aluminate solution in the alumina industry. The mixing process in three types of seed precipitation tanks (Robin, Ekato, and improved Ekato) stirred with multiple impellers was compared by using computational fluid dynamics, respectively. The flow field, solid distribution, mixing time, and power consumption were numerically simulated by adopting a Eulerian granular multiphase model and a standard k- ɛ turbulence model. A steady multiple reference frame approach was used to represent impeller rotation. Compared with the Robin tank, the Ekato tank can generate an axial circulation loop, which is better for fluid mixing and solid suspension; meanwhile about half of the power can be saved. With future improvements in the Ekato tank, the fluid mixing and exchanging can be enhanced under the interaction of a lengthened Intermig impeller coupled with sloped baffles. With a little increase in power consumption, the maximum of the relative solid concentration difference in the whole tank can be maintained within 3%, which meets the design requirement.

Numerical simulation experiments were conducted to delineate the influence of in situ deforestation data on episodic rainfall by comparing two ensembles of five 5-day integrations performed with a recent version of the Goddard Laboratory for Atmospheres General Circulation Model (GCM) that has a simple biosphere model (SiB). The first set, called control cases, used the standard SiB vegetation cover (comprising 12 biomes) and assumed a fully forested Amazonia, while the second set, called deforestation cases, distinguished the partially deforested regions of Amazonia as savanna. Except for this difference, all other initial and prescribed boundary conditions were kept identical in both sets of integrations. The differential analyses of these five cases show the following local effects of deforestation. (1) A discernible decrease in evapotranspiration of about 0.80 mm/d (roughly 18%) that is quite robust in the averages for 1-, 2-, and 5-day forecasts. (2) A decrease in precipitation of about 1.18 mm/d (roughly 8%) that begins to emerge even in 1-2 day averages and exhibits complex evolution that extends downstream with the winds. (3) A significant decrease in the surface drag force (as a consequence of reduced surface roughness of deforested regions) that, in turn, affects the dynamical structure of moisture convergence and circulation. The surface winds increase significantly during the first day, and thereafter the increase is well maintained even in the 2- and 5-day averages.

Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 20011. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds NRC [2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path and the "semi-direct" effect on cloud coverage. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect, is even more complex, especially for mixed-phase convective clouds. ln this paper, a cloud-resolving model (CRM) with detailed spectral-bin microphysics was used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: South Florida, Oklahoma and the Central Pacific. In all three cases, rain reaches the ground earlier for the low CCN (clean) case. Rain suppression is also evident in all three cases with high CCN (dirty) case. However, this suppression only occurs during the first hour of the simulations. During the mature stages of the simulations, the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case, to almost no effect in the Florida case, to rain enhancement in the Pacific case. These results show the complexity of aerosol interactions with convection.

Bias correction of meteorological variables from climate model simulations is a routine strategy for circumventing known limitations of state-of-the-art general circulation models. Although the assessment of climate change impacts often depends on the joint variability of multiple variables, commonly used bias correction methodologies treat each variable independently, and do not consider the relationship among variables. Independent bias correction can therefore produce non-physical corrections and may fail to capture important multivariate relationships. Here, we introduce a joint bias correction methodology (JBC) and apply it to precipitation (P) and temperature (T) fields from the CMIP5 model ensemble. This approach is based on a general bivariate distribution of P-T, and can be seen as a multivariate extension of the commonly used univariate quantile mapping method. It proceeds by correcting either P or T first and then correcting the other variable conditional upon the first one, both following the concept of the univariate quantile mapping. JBC is shown to reduce model-simulated biases in P-T correlation fields, as well as biases in the mean and variance of P and T. In addition, it overcomes a noted problem with an existing joint P-T correction method, namely that this earlier approach did not yield appreciable improvements in P-T correlation coefficients. JBC, using methods such as the one presented here, thus represents an important step in impacts-based research as it explicitly accounts for inter-variable relationships as part of the bias correction procedure, thereby improving not only the individual distributions of P and T, but critically, their joint distribution.

identify the impact of ice processes, radiation and large-scale influence on cloud-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform types). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by cloud processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.

An atmospheric general circulation model simulation for 1948-1997 of the water budgets for the MacKenzie, Mississippi and Amazon River basins is presented. In addition to the water budget, we include passive tracers to identify the geographic sources of water for the basins, and the analysis focuses on the mechanisms contributing to precipitation recycling in each basin. While each basin s precipitation recycling has a strong dependency on evaporation during the mean annual cycle, the interannual variability of the recycling shows important relationships with the atmospheric circulation. The MacKenzie River basin has only a weak interannual dependency on evaporation, where the variations in zonal moisture transport from the Pacific Ocean can affect the basin water cycle. On the other hand, the Mississippi River basin has strong interannual dependencies on evaporation. While the precipitation recycling weakens with increased low level jet intensity, the evaporation variations exert stronger influence in providing water vapor for convective precipitation at the convective cloud base. High precipitation recycling is also found to be partly connected to warm SSTs in the tropical Pacific Ocean. The Amazon River basin evaporation exhibits small interannual variations, so that the interannual variations of precipitation recycling are related to atmospheric moisture transport from the tropical south Atlantic Ocean. Increasing SSTs over the 50-year period are causing increased easterly transport across the basin. As moisture transport increases, the Amazon precipitation recycling decreases (without real time varying vegetation changes). In addition, precipitation recycling from a bulk diagnostic method is compared to the passive tracer method used in the analysis. While the mean values are different, the interannual variations are comparable between each method. The methods also exhibit similar relationships to the terms of the basin scale water budgets.

The NASA Short ]term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real ]time configuration of the NASA Land Information System (LIS) with the Noah land surface model (LSM). Output from the SPoRT ]LIS run is used to initialize land surface variables for local modeling applications at select National Weather Service (NWS) partner offices, and can be displayed in decision support systems for situational awareness and drought monitoring. The SPoRT ]LIS is run over a domain covering the southern and eastern United States, fully nested within the National Centers for Environmental Prediction Stage IV precipitation analysis grid, which provides precipitation forcing to the offline LIS ]Noah runs. The SPoRT Center seeks to expand the real ]time LIS domain to the entire Continental U.S. (CONUS); however, geographical limitations with the Stage IV analysis product have inhibited this expansion. Therefore, a goal of this study is to test alternative precipitation forcing datasets that can enable the LIS expansion by improving upon the current geographical limitations of the Stage IV product. The four precipitation forcing datasets that are inter ]compared on a 4 ]km resolution CONUS domain include the Stage IV, an experimental GOES quantitative precipitation estimate (QPE) from NESDIS/STAR, the National Mosaic and QPE (NMQ) product from the National Severe Storms Laboratory, and the North American Land Data Assimilation System phase 2 (NLDAS ]2) analyses. The NLDAS ]2 dataset is used as the control run, with each of the other three datasets considered experimental runs compared against the control. The regional strengths, weaknesses, and biases of each precipitation analysis are identified relative to the NLDAS ]2 control in terms of accumulated precipitation pattern and amount, and the impacts on the subsequent LSM spin ]up simulations. The ultimate goal is to identify an alternative precipitation forcing dataset that can best support an

Meiyu frontal system that formed and moved over the Huai River basin of China on 7-8 July 2007 is investigated using weather radar observations, Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and CloudSat Cloud Profiling Radar measurements, and brightness temperatures from the MTSAT-1R satellite. These results are used to evaluate cloud-resolving simulations performed using the Weather Research and Forecasting (WRF) model. Sensitivity experiments are conducted to explore impacts of cloud microphysics and radiation on the cloud and precipitation structure. At its mature stage, the observed convective system consisted of a west-east oriented leading convective line with stratiform precipitating and non-precipitating cloud regions trailing off to the north and east. While the cloud system extending hundreds kilometers from west to east, the widths of the convective and stratiform raining regions are of 10-20 km and 100-200 km, respectively. During the system's development stage, newer convection occurred on the western edge of the convective line. The convective centers progressed through a period of rapid growth when propagated eastward, with echo tops penetrating to maximum heights of 16-km, then decreasing to height of 13-km, which corresponds to the height of the stratiform precipitating cloud top with which the convective elements merged at the end of their lifetimes. Results from four simulations are analyzed: CONTROL, Lin, Thompson, and noRad. The three sensitivity experiments are identical to CONTROL except that the Lin and Thompson simulations employ the 1-moment microphysics schemes of Lin and Thompson, respectively, rather than the 2-moment microphysics scheme of Morrison as in CONTROL, and the noRad simulation turns off the radiative cooling/warming effect. The CONTROL reasonably reproduces not only the magnitude and spatial distribution of the accumulated surface precipitation, but also the evolution of the leading convective lines and

At the request of the Intergovernmental Panel on Climate Change (IPCC), simulations of 20th-century climate have been performed recently with some 20 global coupled ocean-atmosphere models. In view of its central importance for biological and socio-economic systems, model-simulated continental precipitation is evaluated relative to three observational estimates at both global and regional scales. Many models are found to display systematic biases, deviating markedly from the observed spatial variability and amplitude/phase of the seasonal cycle. However, the point-wise ensemble mean of all the models usually shows better statistical agreement with the observations than does any single model. Deficiencies of current models that may be responsible for the simulatedprecipitation biases as well as possible reasons for the improved estimate afforded by the multi-model ensemble mean are discussed. Implications of these results for water-resource managers also are briefly addressed.

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model for different environmental conditions, i.e., the South China Sea Monsoon Experiment (SCSMEX), CRYSTAL-FACE, and KAWJEX are compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and as well as cloud observations from the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. The model presents large discrepancies in rain spectrum and vertical hydrometer profiles. The discrepancy in the precipitation field is also consistent with the cloud and radiation observations. The study will focus on the effects of large scale forcing and microphysics to the simulated model- observation discrepancies.

Dissolved CO2 during geological CO2 storage may react with minerals in fractured rocks or confined aquifers and cause mineral precipitation. The overall rate of reaction can be affected by coupled processes among hydrodynamics, transport, and reactions at pore-scale. Pore-scale models of coupled fluid flow, reactive transport, and CaCO3 precipitation and dissolution are applied to account for transient experimental results of CaCO3 precipitation and dissolution under highly supersaturated conditions in a microfluidic pore network (i.e., micromodel). Pore-scale experiments in the micromodel are used as a basis for understanding coupled physics of systems perturbed by geological CO2 injection. In the micromodel, precipitation is induced by transverse mixing along the centerline in pore bodies. Overall, the pore-scale model qualitatively captured the governing physics of reactions such as precipitate morphology, precipitation rate, and maximum precipitation area in first few pore spaces. In particular, we found that proper estimation of the effective diffusion coefficient and the reactive surface area is necessary to adequately simulateprecipitation and dissolution rates. As the model domain increases, the effect of flow patterns affected by precipitation on the overall reaction rate also increases. The model is also applied to account for the effect of different reaction rate laws on mineral precipitation and dissolution at pore-scale. Reaction rate laws tested include the linear rate law, nonlinear power law, and newly-developed rate law based on in-situ measurements at nano scale in the literature. Progress on novel methods for upscaling pore-scale models for reactive transport are discussed, and are being applied to mineral precipitation patterns observed in natural analogues. H.Y. and T. D. were supported as part of the Center for Frontiers of Subsurface Energy Security, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of

The Tropical Warm Pool.International Cloud Experiment (TWP ]ICE) provided extensive observational data sets designed to initialize, force, and constrain atmospheric model simulations. In this first of a two ]part study, precipitation and cloud structures within nine cloud ]resolving model simulations are compared with scanning radar reflectivity and satellite infrared brightness temperature observations during an active monsoon period from 19 to 25 January 2006. Seven of nine simulations overestimate convective area by 20% or more leading to general overestimation of convective rainfall. This is balanced by underestimation of stratiform rainfall by 5% to 50% despite overestimation of stratiform area by up to 65% because of a preponderance of very low stratiform rain rates in all simulations. All simulations fail to reproduce observed radar reflectivity distributions above the melting level in convective regions and throughout the troposphere in stratiform regions. Observed precipitation ]sized ice reaches higher altitudes than simulatedprecipitation ]sized ice despite some simulations that predict lower than observed top ]of ]atmosphere infrared brightness temperatures. For the simulations that overestimate radar reflectivity aloft, graupel is the cause with one ]moment microphysics schemes whereas snow is the cause with two ]moment microphysics schemes. Differences in simulated radar reflectivity are more highly correlated with differences in mass mean melted diameter (Dm) than differences in ice water content. Dm is largely dependent on the mass ]dimension relationship and gamma size distribution parameters such as size intercept (N0) and shape parameter (m). Having variable density, variable N0, or m greater than zero produces radar reflectivities closest to those observed.

Urban stormwater from simulated rainfall on three different landuses in Queensland State, Australia (residential, industrial, commercial) was analysed for heavy metals and physico-chemical parameters such as Dissolved Organic Carbon (DOC) and Total Suspended Solids (TSS). Rainfall events were simulated using a specially designed rainfall simulator for paved surfaces. Event mean concentration samples were separated into five different particle sizes and analysed individually for eight metal elements (Zn, Fe, Cr, Cd, Cu, Al, Mn and Pb). Multivariate data analysis was carried out for the data thus generated. It was found that DOC and TSS influence the distribution of the metals in the different particle size classes. Zn was correlated with DOC at all three sites. Similarly, Pb, Fe and Al were correlated with TSS at all sites. The distribution of Cu was found to vary between the three sites, whilst Cd concentrations were too low to assess any relationships with other parameters. No correlation between Electrical Conductivity (EC), pH and heavy metals was found at the three sites. The identification of physico-chemical parameters influencing the distribution process kinetics of heavy metals in urban stormwater will significantly enhance the efficiency of urban stormwater management systems. PMID:15939127

In preparation for the launch of Solar Orbiter in 2017 or 2018, we have begun development of the Heavy Ion Sensor (HIS) as a part of the Solar Wind Analyzer (SWA) instrument suite. HIS is capable of making full three-dimensional distribution measurements of the heavy ion population in the solar wind every 5 minutes. Specifically, it does this by differentiating the solar wind into energy-per-charge bins, using an electrostatic analyzer (ESA), then flying the particle through a time-of-flight (TOF) chamber to measure their speeds, and finally collecting the particles in a solid-state detector (SSD) to measure the particles' final energy. The particles interact with carbon foils at the start and end of the TOF chamber and in the dead layer of the SSD, creating uncertainty in the measurement of TOF and energy. This uncertainty can be estimated through the Stopping and Range of Ions in Matter (SRIM) simulations. Additionally, the SSD is unlikely to observe the full kinetic energy of heavy ions due to the pulse height defect and electronic noise. In our Monte Carlo simulation, we characterize the PHD by an average energy loss [Daoudi et al., 2009] and a spread of the observed energy distribution, which are both mass and initial energy dependent. Monte Carlo simulation provides a fast and low cost methodology to develop the instrument and characterize its predicted behavior under varying solar wind conditions.

Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean

To help understand heavy gas releases and simulate the resultant dispersion, we have developed a three-dimensional finite element model called FEM3 and an improved version names FEM3A for solving the time dependent conservation equations based on generalized anelastic approximation. Recent enhancements to the model to include the treatment of dispersion scenarios involving density variations much larger than the liquefied natural gas range and an advanced turbulence submodel based on the buoyancy-extended transport equations. This paper presents the main features of the present model FEM3C and numerical results from the simulations of a field-scale LNG spill experiment.

The Heavy Ion Fusion Science Virtual National Laboratory (HIFS-VNL) is a collaboration of Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, and Princeton Plasma Physics Laboratory. These laboratories, in cooperation with researchers at other institutions, are carrying out a coordinated effort to apply intense ion beams as drivers for studies of the physics of matter at extreme conditions, and ultimately for inertial fusion energy. Progress on this endeavor depends upon coordinated application of experiments, theory, and simulations. This paper describes the state of the art, with an emphasis on the coordination of modeling and experiment; developments in the simulation tools, and in the methods that underly them, are also treated.

The Heavy Ion Fusion Science Virtual National Laboratory (HIFS-VNL) is a collaboration of Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, and Princeton Plasma Physics Laboratory. These laboratories, in cooperation with researchers at other institutions, are carrying out a coordinated effort to apply intense ion beams as drivers for studies of the physics of matter at extreme conditions, and ultimately for inertial fusion energy. Progress on this endeavor depends upon coordinated application of experiments, theory, and simulations. This paper describes the state of the art, with an emphasis on the coordination of modeling and experiment; developments in the simulation tools, and in the methods that underly them, are also treated.

Mid-latitude precipitation over land exhibits a high degree of variability due to the complex interaction of governing atmospheric processes with coastlines, the heterogeneous land surface, and orography. General circulation models (GCMs) have traditionally shown limited ability in capturing variability in the mesoscale range (here ~50-500 km), due to their low resolution. Recent advances in resolution have provided ensembles of multidecadal climate simulations with GCMs using ~25 km grid spacing. Here, we assess this class of GCM simulations, from the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) campaign. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products (e.g. from the Global Precipitation Climatology Project, GPCP) are invaluable for assessing large-scale precipitation features, but may not sufficiently resolve mesoscale structures. In the absence of alternative estimates, the intercomparison of specialised, regional observational datasets may be the only way to gain insight into the uncertainties associated with these observations. We focus on three mid-latitude continental regions where gridded precipitation observations based on higher-density gauge networks are available, complementing the global data sets: Europe (with a particular emphasis on the Alps), South and East Asia, and the continental US. Additional motivation, and opportunity, arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean precipitation/evaporation may be up to 10 Wm-2 (about 0.35 mm day-1) larger than the estimate obtained from GPCP. While the main part of this discrepancy is thought to be due to the underestimation of remotely-sensed ocean precipitation, there is also considerable uncertainty about 'unobserved' precipitation

Global and regional climate change assessments rely heavily on the general circulation model (GCM) outputs such as provided by the Coupled Model Intercomparison Project phase 5 (CMIP5). Here we evaluate the ability of 25 CMIP5 GCMs to simulate historical precipitation and temperature over central Africa and assess their future projections in the context of historical performance and intermodel and future emission scenario uncertainties. We then apply a statistical bias correction technique to the monthly climate fields and develop monthly downscaled fields for the period of 1948-2099. The bias-corrected and downscaled data set is constructed by combining a suite of global observation and reanalysis-based data sets, with the monthly GCM outputs for the 20th century, and 21st century projections for the medium mitigation (representative concentration pathway (RCP)45) and high emission (RCP85) scenarios. Overall, the CMIP5 models simulate temperature better than precipitation, but substantial spatial heterogeneity exists. Many models show limited skill in simulating the seasonality, spatial patterns, and magnitude of precipitation. Temperature projections by the end of the 21st century (2070-2099) show a robust warming between 2 and 4°C across models, whereas precipitation projections vary across models in the sign and magnitude of change (-9% to 27%). Projected increase in precipitation for a subset of models (single model ensemble (SME)) identified based on performance metrics and causal mechanisms are slightly higher compared to the full multimodel ensemble (MME) mean; however, temperature projections are similar between the two ensemble means. For the near-term (2021-2050), neither the historical performance nor choice of models is related to the precipitation projections, indicating that natural variability dominated any signal. With fewer models, the "blind" MME approach will have larger uncertainties in future precipitation projections compared to projections

The origin of the selected area electron diffraction (SAED) patterns from needle/rod-like metastable precipitates embedded in {alpha}-Al matrix in Al-Mg-Si alloys have been studied via an example of {beta}'' phase. In addition, the SAED pattern from {beta}'' phase has been simulated with significant improvement in comparison with the previous simulations. Three important factors, i.e. the 12 crystallographically equivalent variants of {beta}'' phase in the {alpha}-Al matrix due to the highly symmetric f.c.c. structure of {alpha}-Al, the coherence between {beta}'' phase and the {alpha}-Al matrix, and the double diffractions from the {alpha}-Al matrix and {beta}'' phase, are proved to contribute to the special square-shaped features in the SAED patterns from {beta}'' phase and thus fully taken into account in the simulation. An improved but simplified method for simulating the SAED patterns from needle/rod-like metastable precipitates has been developed. This method is further verified by simulating the SAED pattern from Q phase. The simulated SAED patterns from both {beta}'' and Q phases fit the experimentally determined patterns very well. - Highlights: {yields}An improved method has been developed to simulate the SADPs of Al alloys. {yields}The formation mechanism of SADPs of Al alloys has been systemically studied. {yields}Double diffraction contributes to the formation of the SADPs of Al alloys.

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscaling of global climate model (GCM) output for air quality applications under a changing climate. In this study we downscale the NCEP-Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis using three continuous 20-year WRF simulations: one simulation without interior grid nudging and two using different interior grid nudging methods. The biases in 2-m temperature and precipitation for the simulation without interior grid nudging are unreasonably large with respect to the North American Regional Reanalysis (NARR) over the eastern half of the contiguous United States (CONUS) during the summer when air quality concerns are most relevant. This study examines how these differences arise from errors in predicting the large-scale atmospheric circulation. It is demonstrated that the Bermuda high, which strongly influences the regional climate for much of the eastern half of the CONUS during the summer, is poorly simulated without interior grid nudging. In particular, two summers when the Bermuda high was west (1993) and east (2003) of its climatological position are chosen to illustrate problems in the large-scale atmospheric circulation anomalies. For both summers, WRF without interior grid nudging fails to simulate the placement of the upper-level anticyclonic (1993) and cyclonic (2003) circulation anomalies. The displacement of the large-scale circulation impacts the lower atmosphere moisture transport and precipitable water, affecting the convective environment and precipitation. Using interior grid nudging improves the large-scale circulation aloft and moisture transport/precipitable water anomalies, thereby improving the simulated 2-m temperature and precipitation

Land use and land cover (LULC) over Africa have changed substantially over the last 60 years and this change has been proposed to affect monsoon circulation and precipitation. This study examines the uncertainties of model simulated response in the African monsoon system and Sahel precipitation due to LULC change using a set of regional model simulations with different combinations of land surface and cumulus parameterization schemes. Although the magnitude of the response covers a broad range of values, most of the simulations show a decline in Sahel precipitation due to the expansion of pasture and croplands at the expense of trees and shrubs and an increase in surface air temperature. The relationship between the model responses to LULC change and the climatologists of the control simulations is also examined. Simulations that are climatologically too dry or too wet compared to observations and reanalyses have weak response to land use change because they are in moisture or energy limited regimes respectively. The ones that lie in between have stronger response to the LULC changes, showing a more significant role in land-atmosphere interactions. Much of the change in precipitation is related to changes in circulation, particularly to the response of the intensity and latitudinal position of the African Easterly Jet, which varies with the changes in meridional surface temperature gradients. The study highlights the need for measurements of the surface fluxes across the meridional cross-section of the Sahel to evaluate models and thereby allowing human impacts such as land use change on the monsoon to be projected more realistically.

[1]Previous studies on electromagnetic ion cyclotron (EMIC) waves as a possible cause of relativistic electron precipitation (REP) mainly focus on the time evolution of the trapped electron flux. However, directly measured by balloons and many satellites is the precipitating flux as well as its dependence on both time and energy. Therefore, to better understand whether pitch angle scattering by EMIC waves is an important radiation belt electron loss mechanism and whether quasi-linear theory is a sufficient theoretical treatment, we simulate the quasi-linear wave-particle interactions for a range of parameters and generate energy spectra, laying the foundation for modeling specific events that can be compared with balloon and spacecraft observations. We show that the REP energy spectrum has a peaked structure, with a lower cutoff at the minimum resonant energy. The peak moves with time toward higher energies and the spectrum flattens. The precipitating flux, on the other hand, first rapidly increases and then gradually decreases. We also show that increasing wave frequency can lead to the occurrence of a second peak. In both single- and double-peak cases, increasing wave frequency, cold plasma density or decreasing background magnetic field strength lowers the energies of the peak(s) and causes the precipitation to increase at low energies and decrease at high energies at the start of the precipitation. PMID:26167427

A computer model to simulate the processes of charge injection and migration through DNA after irradiation by a heavy charged particle was developed. The most probable sites of charge injection were obtained by merging spatial models of short DNA sequence and a single 1 GeV/u iron particle track simulated by the code RITRACKS (Relativistic Ion Tracks). Charge migration was simulated by using a quantum-classical nonlinear model of the DNA-charge system. It was found that charge migration depends on the environmental conditions. The oxidative damage in DNA occurring during hole migration was simulated concurrently, which allowed the determination of probable locations of radiation-induced DNA lesions. PMID:26405967

The location and occurrence time of convective rainfalls have attracted great public concern as they can lead to terrible disasters. However, the simulation results of convective rainfalls in the Pearl River Delta region often show significant discrepancies from the observations. One of the major causes lies in the inaccurate geographic distribution of land surface properties used in the model simulation of the heavyprecipitation. In this study, we replaced the default soil and vegetation datasets of Weather Research and Forecasting (WRF) model with two refined datasets, i.e. the GlobCover 2009 (GLC2009) land cover map and the Harmonized World Soil Database (HWSD) soil texture, to investigate the impact of vegetation and soil on the rainfall patterns. The result showed that the simulation patterns of convective rainfalls obtained from the coupled refined datasets are more consistent with the observations than those obtained from the default ones. By using the coupled refined land surface datasets, the overlap ratio of high precipitation districts reached 36.3% with a variance of 28.5 km from the observed maximum rainfall position, while those of the default United States Geological Survey (USGS) dataset and Moderate Resolution Imaging Spectroradiometer (MODIS) dataset are 17.0%/32.8 km and 24.9%/49.0 km, respectively. The simulated total rainfall amount and occurrence time using the coupled refined datasets are the closest to the observed peak values. In addition, the HWSD soil data has improved the accuracy of the simulatedprecipitation amount, and the GLC2009 land cover data also did better in catching the early peak time.

This paper examines the effect of spatially variable initial soil moisture and spatially variable precipitation on predictive uncertainty of simulated catchment scale runoff response in the presence of threshold processes. The underlying philosophy is to use a physically based hydrological model named CATFLOW as a virtual landscape, assuming perfect knowledge of the processes. The model, which in particular conceptualizes preferential flow as threshold process, was developed based on intensive process and parameter studies and has already been successfully applied to simulate flow and transport at different scales and catchments. Study area is the intensively investigated Weiherbach catchment. Numerous replicas of spatially variable initial soil moisture or spatially variable precipitation with the same geostatistical properties are conditioned to observed soil moisture and precipitation data and serve as initial and boundary conditions for the model during repeated simulations. The effect of spatially soil moisture on modeling catchment runoff response was found to depend strongly on average saturation of the catchment. Different realizations of initial soil moisture yielded strongly different hydrographs for intermediate initial soil moisture as well as in dry catchment conditions; in other states the effect was found to be much lower. This is clearly because of the threshold nature of preferential flow as well as the threshold nature of Hortonian production of overland flow. It was shown furthermore that the spatial pattern of a key parameter (macroporosity) that determined threshold behavior is of vast importance for the model response. The estimation of these patterns, which is mostly done based on sparse observations and expert knowledge, is a major source for predictive model uncertainty. Finally, it was shown that the usage of biased, i.e. spatially homogenized precipitation, input during parameter estimation yields a biased model structure, which gives

Soil respiration (Rs) is the second-largest terrestrial carbon (C) flux. Although Rs has been extensively studied across a broad range of biomes, there is surprisingly little consensus on how the spatiotemporal patterns of Rs will be altered in a warming climate with changing precipitation regimes. Here, we present a global synthesis Rs data from studies that have manipulated precipitation in the field by collating studies from 113 increased precipitation treatments, 91 decreased precipitation treatments, and 14 prolonged drought treatments. Our meta-analysis indicated that when the increased precipitation treatments were normalized to 28% above the ambient level, the soil moisture, Rs, and the temperature sensitivity (Q10) values increased by an average of 17%, 16%, and 6%, respectively, and the soil temperature decreased by -1.3%. The greatest increases in Rs and Q10 were observed in arid areas, and the stimulation rates decreased with increases in climate humidity. When the decreased precipitation treatments were normalized to 28% below the ambient level, the soil moisture and Rs values decreased by an average of -14% and -17%, respectively, and the soil temperature and Q10 values were not altered. The reductions in soil moisture tended to be greater in more humid areas. Prolonged drought without alterations in the amount of precipitation reduced the soil moisture and Rs by -12% and -6%, respectively, but did not alter Q10. Overall, our synthesis suggests that soil moisture and Rs tend to be more sensitive to increased precipitation in more arid areas and more responsive to decreased precipitation in more humid areas. The responses of Rs and Q10 were predominantly driven by precipitation-induced changes in the soil moisture, whereas changes in the soil temperature had limited impacts. Finally, our synthesis of prolonged drought experiments also emphasizes the importance of the timing and frequency of precipitation events on ecosystem C cycles. Given these

The effect of PVC-derived chlorine on heavy metal emissions in MSW incineration was investigated using a tubular furnace and simulated MSW spiked with PVCs and heavy metals (Cd, Cr, Cu, and Zn). The authors varied the molar ratio of the chlorine content to that of the heavy metal (Cl/M ratio) from 3--200 as one parameter. The results indicated that the major species found in the fly ash were chlorides of alkaline and alkali-earth metals, whereas those identified in the bottom ash were MgSiO{sub 3}, SiO{sub 2} and some complex aluminates and silicates. The emission of heavy metals and/or their compounds, with extreme and medium volatility, tended to be enhanced within the lower Cl/M range, whereas those with a refractory volatility were likely to be affected within the higher Cl/M range. However, those with an extremely refractory volatility were less affected by an increase of the Cl/M ratio. The variation of speciation and partitioning in MSW combustion as affected by the Cl/M ratio are discussed.

The transmittance signal of a precipitant system measured with a focused laser beam carries associated noise coming from several sources. In this work, we have studied the influence of the focal parameters (wavelength, focal length and prefocused radius of the beam) on the maximum noise reached in equivalent nucleation processes. For this purpose, a simulation program of precipitating systems, designed in FORTRAN 90, has been developed. The program generates simulated transmittances, which are processed by another computer program to extract associated noise. Wide ranges of values of the focal parameters have been analysed, finding relationships between the maximum noise and the focal parameters. They have been justified in connection with the changes observed in the radial parameters, which define the size and shape of the focused path. PMID:11513240

We present the results of numerical studies of the interaction of solar wind ions with the dayside magnetospheric boundary for a southward interplanetary magnetic field (IMF). These studies use the time-dependent electric and magnetic fields predicted by three-dimensional global magnetohydrodynamic (MHD) simulations to compute the trajectories of large samples of solar wind ions launched upstream of the bow shock. Energy-latitude spectra computed from the large scale kinetic (LSK) simulations show that a strong dawn-dusk asymmetry develops in the precipitation of low to middle energy ions over the high-latitude dayside magnetosphere. These results are consistent with statistical studies of DMSP data showing that ion precipitation from the mantle is predominantly seen over the morning and pre-noon sector.

The rheological properties of heavy crude oil have a significant impact on the production, refining and transportation. In this paper, dissipative particle dynamics (DPD) simulations were performed to study the effects of the addition of light crude oil and emulsification on the rheological properties of heavy crude oil. The simulation results reflected that the addition of light crude oil reduced the viscosity effectively. The shear thinning behaviour of crude oil mixtures were becoming less distinct as the increase of the mass fraction of light crude oil. According to the statistics, the shear had an influence on the aggregation and spatial orientation of asphaltene molecules. In addition, the relationship between the viscosity and the oil mass fraction was investigated in the simulations of emulsion systems. The viscosity increased with the oil mass fraction slowly in oil-in-water emulsions. When the oil mass fraction was higher than 50%, the increase became much faster since systems had been converted into water-in-oil emulsions. The equilibrated morphologies of emulsion systems were shown to illustrate the phase inversion. The surfactant-like feature of asphaltenes was also studied in the simulations.

Land use and land cover over Africa have changed substantially over the last sixty years and this change has been proposed to affect monsoon circulation and precipitation. This study examines the uncertainties on the effect of these changes on the African Monsoon system and Sahel precipitation using an ensemble of regional model simulations with different combinations of land surface and cumulus parameterization schemes. Although the magnitude of the response covers a broad range of values, most of the simulations show a decline in Sahel precipitation due to the expansion of pasture and croplands at the expense of trees and shrubs and an increase in surface air temperature. The relationship between the model responses to land use change and the climatologies of the control simulations is also examined. Simulations that are climatologically too dry or too wet compared to observations and reanalyses have weak response to land use change because they are in moisture or energy limited regimes respectively. The ones that lie in between and therefore land-atmosphere interactions play a more significant role have stronger response to the land use and land cover changes. Much of the change in precipitation is related to changes in circulation, particularly to the response of the intensity and latitudinal position of the African Easterly Jet, which varies with the changes in meridional surface temperature gradients. The study highlights the need for measurements of the surface fluxes across the meridional cross-section of the Sahel to evaluate models and thereby allowing human impacts such as land use change on the monsoon to be projected more realistically.

Statistically significant improvements to a 'Poor Man's Ensemble' (PME) of coarse-resolution numeral precipitation forecast for the Australian Snowy Mountains can be achieved using a clustering algorithm. Daily upwind soundings are classified according to one of four clusters, which are employed to adjust the precipitation forecasts using a linear regression. This approach is a type of 'statistical downscaling', in that it relies on a historical relationship between observed and forecast precipitation amounts, and is a computationally cheap and fast way to improve forecast skill. For the 'wettest' class, the root-mean-square error for the one-day forecast was reduced from 26.98 to 17.08 mm, and for the second 'wet' class the improvement was from 8.43 to 5.57 mm. Regressions performed for the two 'dry' classes were not shown to significantly improve the forecast. Statistical measures of the probability of precipitation and the quantitative precipitation forecast were evaluated for the whole of the 2011 winter (May-September). With a 'hit rate' (fraction of correctly-forecast rain days) of 0.9, and a 'false alarm rate' (fraction of forecast rain days which did not occur) of 0.16 the PME forecast performs well in identifying rain days. The precipitation amount is, however systematically under-predicted, with a mean bias of -5.76 mm and RMSE of 12.86 mm for rain days during the 2011 winter. To compare the statistically downscaled results with the capabilities of a state of the art numerical prediction system, the WRF model was run at 4 km resolution over the Australian Alpine region for the same period, and precipitation forecasts analysed in a similar manner. It had a hit rate of 0.955 and RMSE of 5.16 mm for rain days. The main reason for the improved performance relative to the PME is that the high resolution of the simulations better captures the orographic forcing due to the terrain, and consequently resolves the precipitation processes more realistically, but

Extremes of weather and climate can have devastating effects on human society and the environment. Understanding past changes in the characteristics of such events, including recent increases in the intensity of heavyprecipitation events over a large part of the Northern Hemisphere land area, is critical for reliable projections of future changes. Given that atmospheric water-holding capacity is expected to increase roughly exponentially with temperature--and that atmospheric water content is increasing in accord with this theoretical expectation--it has been suggested that human-influenced global warming may be partly responsible for increases in heavyprecipitation. Because of the limited availability of daily observations, however, most previous studies have examined only the potential detectability of changes in extreme precipitation through model-model comparisons. Here we show that human-induced increases in greenhouse gases have contributed to the observed intensification of heavyprecipitation events found over approximately two-thirds of data-covered parts of Northern Hemisphere land areas. These results are based on a comparison of observed and multi-model simulated changes in extreme precipitation over the latter half of the twentieth century analysed with an optimal fingerprinting technique. Changes in extreme precipitation projected by models, and thus the impacts of future changes in extreme precipitation, may be underestimated because models seem to underestimate the observed increase in heavyprecipitation with warming. PMID:21331039

The present study analyses the sign, strength, and working mechanism of the vegetation-precipitation feedback over North Africa in middle (6 ka BP) and early Holocene (9 ka BP) simulations using the comprehensive coupled climate-vegetation model CCSM3-DGVM (Community Climate System Model version 3 and a dynamic global vegetation model). The coupled model simulates enhanced summer rainfall and a northward migration of the West African monsoon trough along with an expansion of the vegetation cover for the early and middle Holocene compared to the pre-industrial period. It is shown that dynamic vegetation enhances the orbitally triggered summer precipitation anomaly by approximately 20% in the Sahara-Sahel region (10-25° N, 20° W-30° E) in both the early and mid-Holocene experiments compared to their fixed-vegetation counterparts. The primary vegetation-rainfall feedback identified here operates through surface latent heat flux anomalies by canopy evaporation and transpiration and their effect on the mid-tropospheric African easterly jet, whereas the effects of vegetation changes on surface albedo and local water recycling play a negligible role. Even though CCSM3-DGVM simulates a positive vegetation-precipitation feedback in the North African region, this feedback is not strong enough to produce multiple equilibrium climate-ecosystem states on a regional scale.

The present study analyses the sign, strength and working mechanism of the vegetation-precipitation feedback over North Africa in middle (6 ka BP) and early Holocene (9 ka BP) simulations using the comprehensive coupled climate-vegetation model CCSM3-DGVM. The coupled model simulates enhanced summer rainfall and a northward migration of the West African monsoon trough along with an expansion of the vegetation cover for the early and middle Holocene compared to pre-industrial. It is shown that dynamic vegetation enhances the orbitally triggered summer precipitation anomaly by approximately 20% in the Sahara/Sahel region (10° N-25° N, 20° W-30° E) in both the early and mid-Holocene experiments compared to their fixed-vegetation counterparts. The primary vegetation-rainfall feedback identified here operates through surface latent heat flux anomalies by canopy evaporation and transpiration and their effect on the mid-tropospheric African Easterly Jet, whereas the effects of vegetation changes on surface albedo and local water recycling play a negligible role. Even though CCSM3-DGVM simulates a positive vegetation-precipitation feedback in the North African region, this feedback is not strong enough to produce multiple equilibrium climate-ecosystem states on a regional scale.

The Large Hadron Collider (LHC) at CERN pushes forward to new regimes in terms of beam energy and intensity. In view of the combination of very energetic and intense beams together with sensitive machine components, in particular the superconducting magnets, the LHC is equipped with a collimation system to provide protection and intercept uncontrolled beam losses. Beam losses could cause a superconducting magnet to quench, or in the worst case, damage the hardware. The collimation system, which is optimized to provide a good protection with proton beams, has shown a cleaning efficiency with heavy-ion beams which is worse by up to two orders of magnitude. The reason for this reduced cleaning efficiency is the fragmentation of heavy-ion beams into isotopes with a different mass to charge ratios because of the interaction with the collimator material. In order to ensure sufficient collimation performance in future ion runs, a detailed theoretical understanding of ion collimation is needed. The simulation of heavy-ion collimation must include processes in which 82+208Pb ions fragment into dozens of new isotopes. The ions and their fragments must be tracked inside the magnetic lattice of the LHC to determine their loss positions. This paper gives an overview of physical processes important for the description of heavy-ion loss patterns. Loss maps simulated by means of the two tools ICOSIM [1,2] and the newly developed STIER (SixTrack with Ion-Equivalent Rigidities) are compared with experimental data measured during LHC operation. The comparison shows that the tool STIER is in better agreement.

Analyses of recently reconstructed and model-simulated Indian May-September precipitation disclose a statistically significant multidecadal variation at the frequency of 40-50 year per cycle during the last half millennium. To understand the mechanism of this variation, we examined the energy and dynamic processes in the atmosphere, and the potential forcings from the sea surface temperature (SST) variations around the globe. Comparisons of paleo-SST and the paleo-precipitationsimulations suggest that the SST is not a significant forcing of the multidecadal variation found in the Indian monsoon precipitation. Instead, analyses suggest that atmospheric processes characterized by phase differences between the meridional enthalpy gradient and poleward eddy enthalpy transport are important to sustain this variation. In this phase relationship, the meridional enthalpy gradient is strengthened by radiative loss in high latitudes. Driven by this enlarged gradient and associated changes in baroclinicity in the mid-latitude atmosphere, more energy is generated in the tropical and subtropical (monsoon) regions and transported poleward. The monsoon is strengthened to allow more energy being transported poleward. The increased enthalpy transport, in turn, weakens the meridional enthalpy gradient and, subsequently, softens the demand for energy production in the monsoon region. The monsoon weakens and the transport decreases. The variation in monsoon precipitation lags that in the meridional enthalpy gradient, but leads that in the poleward heat transport. This phase relationship and underlining chasing process by the heat transport to the gradient sustain this variation at the multidecadal timescale. This mechanism suggests that atmospheric circulation processes can contribute to multidecadal timescale variations in the Indian monsoon precipitation.

Monthly and daily precipitation extremes over La Plata Basin (LPB) are analyzed in the framework of the CLARIS-LPB Project. A review of the studies developed during the project and results of additional research are presented and discussed. Specific aspects of analysis are focused on large-scale versus local processes impacts on the intensity and frequency of precipitation extremes over LPB, and on the assessment of specific wet and dry spell indices and their changed characteristics in future climate scenarios. The analysis is shown for both available observations of precipitation in the region and ad-hoc global and regional models experiments. The Pacific, Indian and Atlantic Oceans can all impact precipitation intensity and frequency over LPB. In particular, considering the Pacific sector, different types of ENSO events (i.e. canonical vs Modoki or East vs Central) have different influences. Moreover, model projections indicate an increase in the frequency of precipitation extremes over LPB during El Niño and La Ninã events in future climate. Local forcings can also be important for precipitation extremes. Here, the feedbacks between soil moisture and extreme precipitation in LPB are discussed based on hydric conditions in the region and model sensitivity experiments. Concerning droughts, it was found that they were more frequent in the western than in the eastern sector of LPB during the period of 1962-2008. On the other hand, observations and model experiments agree in that the monthly wet extremes were more frequent than the dry extremes in the northern and southern LPB sectors during the period 1979-2001, with higher frequency in the south.

As part of an ongoing effort to evaluate THC effects on flow in fractured media, we performed a laboratory experiment and numerical simulations to investigate mineral dissolution and precipitation. To replicate mineral dissolution by condensate in fractured tuff, deionized water equilibrated with carbon dioxide was flowed for 1,500 hours through crushed Yucca Mountain tuff at 94° C. The reacted water was collected and sampled for major dissolved species, total alkalinity, electrical conductivity, and pH. The resulting steady-state fluid composition had a total dissolved solids content of about 140 mg/L; silica was the dominant dissolved constituent. A portion of the steady-state reacted water was flowed at 10.8 mL/hr into a 31.7-cm tall, 16.2-cm wide vertically oriented planar fracture with a hydraulic aperture of 31 microns in a block of welded Topopah Spring tuff that was maintained at 80° C at the top and 130° C at the bottom. The fracture began to seal within five days. A 1-D plug-flow model using the TOUGHREACT code developed at Berkeley Lab was used to simulate mineral dissolution, and a 2-D model was developed to simulate the flow of mineralized water through a planar fracture, where boiling conditions led to mineral precipitation. Predicted concentrations of the major dissolved constituents for the tuff dissolution were within a factor of 2 of the measured average steady-state compositions. The fracture-plugging simulations result in the precipitation of amorphous silica at the base of the boiling front, leading to a hundred-fold decrease in fracture permeability in less than 6 days, consistent with the laboratory experiment. These results help validate the use of the TOUGHREACT code for THC modeling of the Yucca Mountain system. The experiment and simulations indicate that boiling and concomitant precipitation of amorphous silica could cause significant reductions in fracture porosity and permeability on a local scale. The TOUGHREACT code will be used

Precipitation information is crucial for regional hydrological and agricultural climate change impact studies. Regional climate models (RCMs) are suitable tools to provide high spatial resolution precipitation products at regional scales, however, they are usually biased not only in absolute values, but also in reproducing observed spatial patterns. Therefore, bias correction techniques are required to obtain suited meteorological information on regional scale. We present a Copula-based method to correct precipitation fields from the Weather Research and Forecasting (WRF) model by merging modelled fields with gridded observation data. Germany is selected as our research domain. High resolution (7km) WRF simulations are used in this study, which is driven by ERA40 reanalysis data for 1971-2000. REGNIE data from Germany Weather Service (DWD) were used as gridded observation data source (1km/daily) and rescaled to 7km for this application. The critical step of this proposed bias correction approach is the establishment of bivariate Copula models, each of them consists of two marginal distributions and one Copula function. The marginal distributions are used to describe the statistical properties of REGNIE and WRF-ERA40 data, while the theoretical Copula function represents the dependence structure between REGNIE and WRF-ERA40 data. Based on this Copula model, the conditional distribution of REGNIE conditioned on WRF-ERA40 can be derived. To generate bias corrected WRF-ERA40 precipitation, a random sample of possible outcomes is drawn from this conditional distribution. This also allows for a quantitative estimation of the inherent uncertainties. The expectation/median/mode value of the stochastic samples can be used as an estimation of the corrected value. For the application, a split-sampling approach is used. Results show that the marginal distributions of REGNIE and WRF-ERA40 are different which implies deficiencies of the WRF-ERA40 simulations to reproduce the

These observing system simulation experiments investigate the assimilation of satellite-observed water vapor and cloud liquid water data in the initialization of a limited-area primitive equations model with the goal of improving short-range precipitation forecasts. The assimilation procedure presented includes two aspects: specification of an initial cloud liquid water vertical distribution and diabatic initialization. The satellite data is simulated for the next generation of polar-orbiting satellite instruments, the Advanced Microwave Sounding Unit (AMSU) and the High-Resolution Infrared Sounder (HIRS), which are scheduled to be launched on the NOAA-K satellite in the mid-1990s. Based on cloud-top height and total column cloud liquid water amounts simulated for satellite data a diagnostic method is used to specify an initial cloud water vertical distribution and to modify the initial moisture distribution in cloudy areas. Using a diabatic initialization procedure, the associated latent heating profiles are directly assimilated into the numerical model. The initial heating is estimated by time averaging the latent heat release from convective and large-scale condensation during the early forecast stage after insertion of satellite-observed temperature, water vapor, and cloud water formation. The assimilation of satellite-observed moisture and cloud water, together withy three-mode diabatic initialization, significantly alleviates the model precipitation spinup problem, especially in the first 3 h of the forecast. Experimental forecasts indicate that the impact of satellite-observed temperature and water vapor profiles and cloud water alone in the initialization procedure shortens the spinup time for precipitation rates by 1-2 h and for regeneration of the areal coverage by 3 h. The diabatic initialization further reduces the precipitation spinup time (compared to adiabatic initialization) by 1 h.

Transverse beam combining is a cost-saving option employed in many designs for heavy-ion inertial fusion energy drivers. A major area of interest, both theoretically and experimentally, is the resultant transverse phase space dilution during the beam merging process. Currently, a prototype combining experiment is underway at LBNL and we have employed a variety of numerical descriptions to aid in both the initial design of the experiment data. These range from simple envelope codes to detailed 2- and 3-D PIC simulations. We compare the predictions of the different numerical models to each other and to experimental data at different longitudinal positions.

For heavy-ion fusion energy applications, Mark and Yu have derived hydrodynamic models for numerical simulation of energetic pinched-beams including self-pinches and external-current pinches. These pinched-beams are applicable to beam propagation in fusion chambers and to the US High Temperature Experiment. The closure of the Mark-Yu model is obtained with adiabatic assumptions mathematically analogous to those of Chew, Goldberger, and Low for MHD. Features of this hydrodynamic beam model are compared with a kinetic treatment.

Time accurate numerical simulations were performed using the Reynolds-averaged Navier-Stokes (RANS) flow solver OVERFLOW for a heavy lift, slowed-rotor, compound helicopter configuration, tested at the NASA Langley 14- by 22-Foot Subsonic Tunnel. The primary purpose of these simulations is to provide support for the development of a large field of view Particle Imaging Velocimetry (PIV) flow measurement technique supported by the Subsonic Rotary Wing (SRW) project under the NASA Fundamental Aeronautics program. These simulations provide a better understanding of the rotor and body wake flows and helped to define PIV measurement locations as well as requirements for validation of flow solver codes. The large field PIV system can measure the three-dimensional velocity flow field in a 0.914m by 1.83m plane. PIV measurements were performed upstream and downstream of the vertical tail section and are compared to simulation results. The simulations are also used to better understand the tunnel wall and body/rotor support effects by comparing simulations with and without tunnel floor/ceiling walls and supports. Comparisons are also made to the experimental force and moment data for the body and rotor.

Simulating the Space Radiation environment with Monte Carlo Codes, such as FLUKA, requires the ability to model the interactions of heavy ions as they penetrate spacecraft and crew member's bodies. Monte-Carlo-type transport codes use total interaction cross sections to determine probabilistically when a particular type of interaction has occurred. Then, at that point, a distinct event generator is employed to determine separately the results of that interaction. The space radiation environment contains a full spectrum of radiation types, including relativistic nuclei, which are the most important component for the evaluation of crew doses. Interactions between incident protons with target nuclei in the spacecraft materials and crew member's bodies are well understood. However, the situation is substantially less comfortable for incident heavier nuclei (heavy ions). We have been engaged in developing several related heavy ion interaction models based on a Quantum Molecular Dynamics-type approach for energies up through about 5 GeV per nucleon (GeV/A) as part of a NASA Consortium that includes a parallel program of cross section measurements to guide and verify this code development.

We present the results of numerical studies of the interaction of solar wind ions with the dayside magnetospheric boundary for a southward interplanetary magnetic field and two solar wind speeds (250 and 500 km/s) using the results of global magnetohydrodynamics simulations in conjunction with large-scale kinetic calculations. Results of these studies show that a dawn-dusk asymmetry is found in the precipitation of low- to middle-energy ions over the high-latitude dayside magnetosphere. This asymmetry is consistent with statistical studies of DMSP data showing that ion precipitation from the mantle is predominantly seen over the morning and prenoon sector. Analysis of energy-latitude spectra and study of individual particle trajectories from the simulations revealed that low-energy ions can enter the magnetopause at high latitudes in regions where the parallel electric field associated with the magnetopause current is positive and strong enough for the ions to gain energies of the order of the parallel potential drop across the magnetopause. Because the parallel electric field in the Northern Hemisphere is positive in the prenoon sector and negative in the afternoon-evening sector, solar wind ions reaching the magnetopause in these regions are accelerated toward the ionosphere on the dawnside and outward on the duskside, creating the asymmetry in precipitation. The same dawn-dusk asymmetry is found in the Southern Hemisphere because both parallel electric field and magnetic field are reversed in direction.

In this study we investigate possible changes in temperature and precipitation on a regional scale over Africa from 1961 to 2100. We use data from two ensembles of climate simulations, one global and one regional, over the Africa-CORDEX domain. The global ensemble includes eight coupled atmosphere ocean general circulation models (AOGCMs) from the CMIP5 project with horizontal resolution varying from about 1° to 3°, namely CanESM2, CNRM-CM5, HadGEM2-ES, NorESM1-M, EC-EARTH, MIROC5, GFDL-ESM2M and MPI-ESM-LR. In the regional ensemble all 8 AOGCMs are downscaled at the Rossby Centre (SMHI) by a regional climate model - RCA4 at 0.44° resolution. Two forcing scenarios are considered, RCP 4.5 and 8.5. The experimental setup allows us to illustrate how uncertainties in future climate change are related to forcing scenario and to forcing AOGCM at different time periods. Further, we investigate the benefit of the higher horizontal resolution in RCA4 by comparing the results to the coarser driving AOGCM data. The significance of the results is investigated by comparing to i) the model simulated natural variability, and, ii) the biases in the control period. Results dealing with changes in the seasonal cycle of temperature and precipitation are presented. We also address higher-order variability by showing results for changes in temperature extremes and for changes in intensity and frequency of extreme precipitation.

In this study we investigate possible changes in temperature and precipitation on a regional scale over Europe from 1961 to 2100. We use data from three ensembles of climate simulations, one global and two regional ones, over the Europe-CORDEX domain. The global ensemble includes five coupled atmosphere ocean general circulation models (AOGCMs) from the CMIP5 project with horizontal resolution varying from about 1º to 3º, namely CNRM-CM5, HadGEM2-ES, IPSL-CM5A-MR, EC-EARTH and MPI-ESM-LR. In the regional ensembles all 5 AOGCMs are downscaled at the Rossby Centre (SMHI) by a regional climate model - RCA4 at 0.44º (c. 50 km) and at 0.11º (c. 12.5 km) resolution under the forcing scenarios RCP 8.5. The experimental setup allows us to investigate the benefit of the higher horizontal resolution, in RCA4 by comparing the results in the two RCA4 ensembles to the coarser driving AOGCM data. The significance of the results is investigated by comparing to i) the model simulated natural variability, and, ii) the biases in the control period. Results dealing with changes in the seasonal cycle of temperature and precipitation and their relation to changes in the large-scale atmospheric circulation are presented. We also address higher-order variability by showing results for changes in temperature extremes and for changes in intensity and frequency of extreme precipitation.

It is known that besides forcing by synoptic-scale processes, the boundary layer conditions often play a key role for the initiation of convective precipitation. The evolution and conditions of the boundary layer depend considerably on the transformation of the available energy at the Earth's surface into sensible and latent heat fluxes. The soil moisture (SM), besides other factors such as the vegetation coverage, land use and soil type, is one of the main factors governing this energy transformation. Additionally, the availability of humidity in the atmosphere is controlled by a number of processes including land surface processes, which in turn are strongly influenced by spatially variable fields of SM. Thus, an accurate specification of the SM distribution is a critical requirement in the representation of land and surface processes in forecast and climate models. Moreover, soil-atmosphere interactions, in particular, the SM-precipitation feedback, are highly relevant for numerical weather prediction and seasonal forecasting. Despite being a long-standing topic in research, different studies present inconclusive results showing some evidence for positive, negative, and no feedbacks depending on region and investigated period, model characteristics and resolution. Reliable data sets for validation or initialization of model simulations are frequently not at one's disposal; especially the SM is currently one of the least assessed quantities with almost no data from operational monitoring networks available. In summer 2007, the field campaign 'Convective and Orographically-induced Precipitation Study' (COPS) was performed in south-western Germany and eastern France. During COPS an innovative measurement approach using a very high number of different SM sensors was introduced. Each station was equipped with sensors at three different depths (5, 20 and 50cm) simultaneously measuring SM and soil temperature. The COPS data set, which provided suitable observations for

Climate analogues, also denoted Space-For-Time, may be used to identify regions where the present climatic conditions resemble conditions of a past or future state of another location or region based on robust climate variable statistics in combination with projections of how these statistics change over time. The study focuses on assessing climate analogues for Denmark based on current climate data set (E-OBS) observations as well as the ENSEMBLES database of future climates with the aim of projecting future precipitation extremes. The local present precipitation extremes are assessed by means of intensity-duration-frequency curves for urban drainage design for the relevant locations being France, the Netherlands, Belgium, Germany, the United Kingdom, and Denmark. Based on this approach projected increases of extreme precipitation by 2100 of 9 and 21% are expected for 2 and 10 year return periods, respectively. The results should be interpreted with caution as the best region to represent future conditions for Denmark is the coastal areas of Northern France, for which only little information is available with respect to present precipitation extremes. PMID:25714642

Weather generators are stochastic models that produce synthetic long time series of weather data from limited records of historical data with statistically similar characteristics to those of observed. Long timeseries of synthetic weather daily data, especially precipitation, are required as climate inputs to hydrological and agricultural models, in order to evaluate the performance of the associated physical systems. LARS-WG is a semi parametric weather generator that uses flexible semi-empirical distributions for the lengths of wet and dry day series and daily precipitation. On the other hand, k-Nearest Neighbor is a non parametric technique to resample data from historical records by conditioning on the preceding days (feature vector). The model finds the historical number of nearest neighbors of the current weather vector using the Euclidean distance and resamples from it their successors. To preserve the temporal persistence, the model calculates the Euclidean distance of vectors which have similar sequence of wet and dry days. The objective of this study is to evaluate the performance of these two different models in reproducing interannual variability of precipitation in three stations in Germany. Keywords: Weather generator, k-Nearest-Neighbor, LARSWG, daily precipitation

Our goal was to observe and quantify the effects of low, medium and high tidal flooding regimes and various precipitation conditions on both Spartina alterniflora and Typha angustifolia in greenhouse mesocosms. The experiment was maintained for 4 months. Each of 3 tanks (600L) ha...

The Tropical Warm Pool - International Cloud Experiment (TWP-ICE) provided high quality model forcing and observational datasets through which detailed model and observational intercomparisons could be performed. In this first of a two part study, precipitation and cloud structures within nine cloud-resolving model simulations are compared with scanning radar reflectivity and satellite infrared brightness temperature observations during an active monsoon period from 19 to 25 January 2006. Most simulations slightly overestimate volumetric convective rainfall. Overestimation of simulated convective area by 50% or more in several simulations is somewhat offset by underestimation of mean convective rain rates. Stratiform volumetric rainfall is underestimated by 13% to 53% despite overestimation of stratiform area by up to 65% because stratiform rain rates in every simulation are much lower than observed. Although simulations match the peaked convective radar reflectivity distribution at low levels, they do not reproduce the peaked distributions observed above the melting level. Simulated radar reflectivity aloft in convective regions is too high in most simulations. 29 In stratiform regions, there is a large spread in model results with none resembling 30 observed distributions. Above the melting level, observed radar reflectivity decreases 31 more gradually with height than simulated radar reflectivity. A few simulations produce 32 unrealistically uniform and cold 10.8-μm infrared brightness temperatures, but several 33 simulations produce distributions close to observed. Assumed ice particle size 34 distributions appear to play a larger role than ice water contents in producing incorrect 35 simulated radar reflectivity distributions aloft despite substantial differences in mean 36 graupel and snow water contents across models. 37

The Tropical Warm Pool – International Cloud Experiment (TWP-ICE) provided high quality model forcing and observational datasets through which detailed model and observational intercomparisons could be performed. In this first of a two part study, precipitation and cloud structures within nine cloud-resolving model simulations are compared with scanning radar reflectivity and satellite infrared brightness temperature observations during an active monsoon period from 19 to 25 January 2006. Most simulations slightly overestimate volumetric convective rainfall. Overestimation of simulated convective area by 50% or more in several simulations is somewhat offset by underestimation of mean convective rain rates. Stratiform volumetric rainfall is underestimated by 13% to 53% despite overestimation of stratiform area by up to 65% because stratiform rain rates in every simulation are much lower than observed. Although simulations match the peaked convective radar reflectivity distribution at low levels, they do not reproduce the peaked distributions observed above the melting level. Simulated radar reflectivity aloft in convective regions is too high in most simulations. In stratiform regions, there is a large spread in model results with none resembling observed distributions. Above the melting level, observed radar reflectivity decreases more gradually with height than simulated radar reflectivity. A few simulations produce unrealistically uniform and cold 10.8-μm infrared brightness temperatures, but several simulations produce distributions close to observed. Assumed ice particle size distributions appear to play a larger role than ice water contents in producing incorrect simulated radar reflectivity distributions aloft despite substantial differences in mean graupel and snow water contents across models.

Using the WRF model in simulations of shallow and deep precipitating cloud systems, we investigated the sensitivity to aerosols initiating as cloud condensation and ice nuclei. A global climatological dataset of sulfates, sea salts, and dust was used as input for a control experiment. Sensitivity experiments with significantly more polluted conditions were conducted to analyze the resulting impacts to cloud and precipitation formation. Simulations were performed using the WRF model with explicit treatment of aerosols added to the Thompson et al (2008) bulk microphysics scheme. The modified scheme achieves droplet formation using pre-tabulated CCN activation tables provided by a parcel model. The ice nucleation is parameterized as a function of dust aerosols as well as homogeneous freezing of deliquesced aerosols. The basic processes of aerosol activation and removal by wet scavenging are considered, but aerosol characteristic size or hygroscopicity does not change due to evaporating droplets. In other words, aerosol processing was ignored. Unique aspects of this study include the usage of one to four kilometer grid spacings and the direct parameterization of ice nucleation from aerosols rather than typical temperature and/or supersaturation relationships alone. Initial results from simulations of a deep winter cloud system and its interaction with significant orography show contrasting sensitivities in regions of warm rain versus mixed liquid and ice conditions. The classical view of higher precipitation amounts in relatively clean maritime clouds with fewer but larger droplets is confirmed for regions dominated by the warm-rain process. However, due to complex interactions with the ice phase and snow riming, the simulations revealed the reverse situation in high terrain areas dominated by snow reaching the surface. Results of other cloud systems will be summarized at the conference.

Climate change impact assessments of water resources systems require simulations of precipitation and evaporation that exhibit distributional and persistence attributes similar to the historical record. Specifically, there is a need to ensure general circulation model (GCM) simulations of rainfall for the current climate exhibit low-frequency variability that is consistent with observed data. Inability to represent low-frequency variability in precipitation and flow leads to biased estimates of the security offered by water resources systems in a warmer climate. This paper presents a method to postprocess GCM precipitationsimulations by imparting correct distributional and persistence attributes, resulting in sequences that are representative of observed records across a range of time scales. The proposed approach is named nesting bias correction (NBC), the rationale being to correct distributional and persistence bias from fine to progressively longer time scales. In the results presented here, distributional attributes have been represented by order 1 and 2 moments with persistence represented by lag 1 autocorrelation coefficients at monthly and annual time scales. The NBC method was applied to the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mk3.5 and MIROC 3.2 hires rainfall simulations for Australia. It was found that the nesting method worked well to correct means, standard deviations, and lag 1 autocorrelations when the biases in the raw GCM outputs were not too large. While the bias correction improves the representation of distributional and persistence attributes at the time scales considered, there is room for representation of longer-term persistence by extending to time scales longer than a year.

The behavior of smoke injected into the atmosphere by massive fires that might follow a nuclear war was simulated. Studies with a three-dimensional global atmospheric circulation model showed that heating of the smoke by sunlight would be important and might produce several effects that would decrease the efficiency with which precipitation removes smoke from the atmosphere. The heating gives rise to vertical motions that carry smoke well above the original injection height. Heating of the smoke also causes the tropopause, which is initially above the smoke, to reform below the heated smoke layer. Smoke above the tropopause is physically isolated from precipitation below. Consequently, the atmospheric residence time of the remaining smoke is greatly increased over the prescribed residence times used in previous models of nuclear winter.

A comprehensive space-borne radar simulator has been developed to support active microwave sensor satellite missions. The two major objectives of this study are: 1) to develop a radar simulator optimized for the Dual-frequency Precipitation Radar (KuPR and KaPR) on the Global Precipitation Measurement Mission satellite (GPM-DPR) and 2) to generate the synthetic test datasets for DPR algorithm development. This simulator consists of two modules: a DPR scanning configuration module and a forward module that generates atmospheric and surface radar observations. To generate realistic DPR test data, the scanning configuration module specifies the technical characteristics of DPR sensor and emulates the scanning geometry of the DPR with a inner swath of about 120 km, which contains matched-beam data from both frequencies, and an outer swath from 120 to 245 km over which only Ku-band data will be acquired. The second module is a forward model used to compute radar observables (reflectivity, attenuation and polarimetric variables) from input model variables including temperature, pressure and water content (rain water, cloud water, cloud ice, snow, graupel and water vapor) over the radar resolution volume. Presently, the input data to the simulator come from the Goddard Cumulus Ensemble (GCE) and Weather Research and Forecast (WRF) models where a constant mass density is assumed for each species with a particle size distribution given by an exponential distribution with fixed intercept parameter (N0) and a slope parameter (Λ) determined from the equivalent water content. Although the model data do not presently contain mixed phase hydrometeors, the Yokoyama-Tanaka melting model is used along with the Bruggeman effective dielectric constant to replace rain and snow particles, where both are present, with mixed phase particles while preserving the snow/water fraction. For testing one of the DPR retrieval algorithms, the Surface Reference Technique (SRT), the simulator uses

We report preliminary results on sputtering of a lunar regolith simulant at room temperature by singly and multiply charged solar wind ions using quadrupole and time-of-flight (TOF) mass spectrometry approaches. Sputtering of the lunar regolith by solar-wind heavy ions may be an important particle source that contributes to the composition of the lunar exosphere, and is a possible mechanism for lunar surface ageing and compositional modification. The measurements were performed in order to assess the relative sputtering efficiency of protons, which are the dominant constituent of the solar wind, and less abundant heavier multicharged solar wind constituents, which have higher physical sputtering yields than same-velocity protons, and whose sputtering yields may be further enhanced due to potential sputtering. Two different target preparation approaches using JSC-1A AGGL lunar regolith simulant are described and compared using SEM and XPS surface analysis.

Meteorological observations over the Tibetan Plateau (TiP) are scarce, and precipitation estimations over this remote region are difficult. The constantly improving capabilities of numerical weather prediction (NWP) models offer the opportunity to reduce this problem by providing precipitation fields and other meteorological variables of high spatial and temporal resolution. Longer time periods of years to decades can be simulated by NWP models by successive model runs of shorter periods, which can be described by the term "regional atmospheric reanalysis". In this paper, we assess the Weather Research and Forecasting (WRF) models capacity in retrieving rain- and snowfall on the TiP in such a configuration using a nested approach: the simulations are conducted with three nested domains at spatial resolutions of 30, 10, and 2 km. A validation study is carried out for a one-month period with a special focus on one-week (22-28 October 2008), during which strong rain- and snowfall was observed on the TiP. The output of the model in each resolution is compared to the Tropical Rainfall Measuring Mission (TRMM) data set for precipitation and to the Moderate Resolution Imaging Spectroradiometer (MODIS) data set for snow extent. TRMM and WRF data are then compared to weather-station measurements. Our results suggest an overall improvement from WRF over TRMM with respect to weather-station measurements. Various configurations of the model with different nesting and forcing strategies, as well as physical parameterisation schemes are compared to propose a suitable design for a regional atmospheric reanalysis over the TiP. The WRF model showed good accuracy in simulating snow- and rainfall on the TiP for a one-month simulation period. Our study reveals that there is nothing like an optimal model strategy applicable for the high-altitude TiP, its fringing high-mountain areas of extremely complex topography and the low-altitude land and sea regions from which much of the

Electron clouds and rising desorbed gas pressure limit the performance of many existing accelerators and, potentially, that of future accelerators including heavy-ion warm-dense matter and fusion drivers. For the latter, self-consistent simulation of the interaction of the heavy-ion beam(s) with the electron cloud is necessary. To this end, we have merged the two codes WARP (HIF accelerator code) and POSINST (high-energy e-cloud build-up code), and added modules for neutral gas molecule generation, gas ionization, and electron tracking algorithms in magnetic fields with large time steps. The new tool is being benchmarked against the High-Current Experiment (HCX) and good agreement has been achieved. The simulations have also aided diagnostic interpretation and have identified unanticipated physical processes. We present the "roadmap" describing the different modules and their interconnections, along with detailed comparisons with HCX experimental results, as well as a preliminary application to the modeling of electron clouds in the Large Hadron Collider.

The South Asian High (SAH) and precipitation over East Asia simulated by 11 coupled GCMs associated with the forthcoming Intergovernmental Panel on Climate Change’s (IPCC) 4th Assessment Report are evaluated. The seasonal behavior of the SAH is presented for each model. Analyses of the results show that all models are able to reproduce the seasonal cycle of the SAH. Locations of the SAH center are also basically reproduced by these models. All models underestimate the intensity and the extension of coverage in summer. The anomalous SAH can be divided into east and west modes according to its longitudinal position in summer on the interannual timescale, and the composite anomalies of the observed precipitation for these two modes tend to have opposite signs over East Asia. However, only several coupled GCMs can simulate the relationship between rainfall and SAH similar to the observed one, which may be associated with the bias in simulation of the subtropical anticyclone over the West Pacific (SAWP) at 500 hPa. In fact, it is found that any coupled GCM, that can reproduce the reasonable summer mean state of SAWP and the southward (northward) withdrawal (extension) for the east (west) mode of SAH as compared to the observed, will also simulate similar rainfall anomaly patterns for the east and west SAH modes over East Asia. Further analysis indicates that the observed variations in the SAH, SAWP and rainfall are closely related to the sea surface temperature (SST) over the equatorial tropical Pacific. Particularly, some models cannot simulate the SAWP extending northward in the west mode and withdrawing southward in the east mode, which may be related to weak major El Niño or La Niña events. The abilities of the coupled GCMs to simulate the SAWP and ENSO events are associated partly with their ability to reproduce the observed relationship between SAH and the rainfall anomaly over East Asia.

Cloud-aerosol remain one of the largest uncertainties in climate modeling. Many of the postulated cloud-aerosol interactions involve precipitation to limit cloud size and life time, in particular for barely precipitating shallow cumulus clouds. If the precipitation exceeds a certain threshold, it will create feedback on the cloud field through cold pools and mesoscale organization. Such mesoscale responses have mostly been ignored so far in the discussion of aerosol indirect effects. We study the sensitivity of trade wind cumulus clouds to perturbations in cloud droplet number concentrations. Over time, the cloud system approaches a radiative-convective equilibrium state. The transient behavior and the properties of the near-equilibrium cloud field depend on the microphysical state and therefore on the cloud droplet number density. The primary response of the cloud field to changes in the cloud droplet number density is deepening of the cloud layer, and results in a shorter cloud life time. If the atmospheric time scales are long enough compared to the microphysical time scales, the cloud field may reach a near-equilibrium regime. In this regime, the decrease in cloud cover compensates much of the brightening of the clouds, and the overall effect on the albedo is small.

Extreme precipitation events over India have resulted in loss of human lives and damaged infrastructures, food crops, and lifelines. The inability of climate models to credibly project precipitation extremes in India has not been helpful to longer-term hazards resilience policy. However, there have been claims that finer-resolution and regional climate models may improve projections. The claims are examined as hypotheses by comparing models with observations from 1951-2005. This paper evaluates the reliability of the latest generation of general circulation models (GCMs), Coupled Model Intercomparison Project Phase 5 (CMIP5), specifically a subset of the better performing CMIP5 models (called "BEST-GCM"). The relative value of finer-resolution regional climate models (RCMs) is examined by comparing Coordinated Regional Climate Downscaling Experiment (CORDEX) South Asia RCMs ("CORDEX-RCMs") versus the GCMs used by those RCMs to provide boundary conditions, or the host GCMs ("HOST-GCMs"). Ensemble mean of BEST-GCMs performed better for most of the extreme precipitation indices than the CORDEX-RCMs or their HOST-GCMs. Weaker performance shown by ensemble mean of CORDEX-RCMs is largely associated with their high intermodel variation. The CORDEX-RCMs occasionally exhibited slightly superior skills compared to BEST-GCMs; on the whole RCMs failed to significantly outperform GCMs. Observed trends in the extremes were not adequately captured by any of the model ensembles, while neither the GCMs nor the RCMs were determined to be adequate to inform hydrologic design.

Towards a better insight into orbital-scale changes in global monsoon, here we examine global monsoon area (GMA) and precipitation (GMP) as well as GMP intensity (GMPI) in the mid-Holocene, approximately 6,000 years ago, using all available numerical experiments from the Paleoclimate Modelling Intercomparison Project. Compared to the reference period, both the mid-Holocene GMA and GMP increased in the majority of the 35 models chosen for analysis according to their ability, averaging 5.5 and 4.2 %, respectively, which were mainly due to the increase in monsoon area and precipitation over the boreal land and austral ocean. The mid-Holocene GMPI decreased in most models and by an average of 1.2 %, mainly due to the decrease in monsoon precipitation intensity over the boreal ocean and austral land. The mid-Holocene GMA, GMP, and GMPI all showed opposite changes both between the land and ocean in the northern or southern hemisphere and between the boreal and austral land or ocean. Orbital-induced changes in large-scale meridional temperature gradient and land-sea thermal contrast are the underlying mechanisms, and the presence of an interactive ocean has an amplifying effect in the boreal land monsoon areas overall. Qualitatively, the model-data comparison indicates agreement in the boreal land monsoon areas and South America but disagreement in southern Africa and northern Australia.

Running simulations is an involved process taking many hours of computational time to complete. With the advent of cluster computing and parallel processing, problems may be solved in much less time compared to those run in serial. Specifically, NVIDIA released the parallel computing platform CUDA in 2007 giving researchers and programmers access to the GPU to solve generalized problems, and not those of just images.In current research, code has previously been developed to study the interaction of the heliosphere and heavy atoms from the local interstellar medium.Ionized species of hydrogen, helium and other heavy atoms are deflected by the heliosphere where as the neutral species are relatively unimpeded. Charge exchange of these neutral particles may occur between ionized species originating from the solar wind or other populations of pickup ions (PUI) modifying the shape and properties of the heliosphere, compared to one without neutrals. The details of the charge exchange interaction are element dependent and need to be investigated one by one. Current research has studied the interaction of local interstellar hydrogen with the heliosphere quite extensively with theory, simulations and modeling.Since hydrogen is the most abundant element care must be taken when coupling MHD equations with the charge exchange interactions. Simulation code has been developed to account for this dynamic problem and they have shown that the shape of the heliosphere is affected by this. Interstellar atoms heavier than hydrogen interacting with the heliosphere has been looked at as well, but not nearly with as much detail or sophisticated models as hydrogen. The heavy atom data collected by IBEX has in this sense been under-utilized by models.Previously, the simulation was computed with the use of MPI (Message Passing Interface) for parallelization. This approach provided a decrease in computational time. However, CUDA enables the programmer to take advantage of the computer

The medium-heavy oil (viscous oil) resources in the Alaska North Slope are estimated at 20 to 25 billion barrels. These oils are viscous, flow sluggishly in the formations, and are difficult to recover. Recovery of this viscous oil requires carefully designed enhanced oil recovery processes. Success of these recovery processes is critically dependent on accurate knowledge of the phase behavior and fluid properties, especially viscosity, of these oils under variety of pressure and temperature conditions. This project focused on predicting phase behavior and viscosity of viscous oils using equations of state and semi-empirical correlations. An experimental study was conducted to quantify the phase behavior and physical properties of viscous oils from the Alaska North Slope oil field. The oil samples were compositionally characterized by the simulated distillation technique. Constant composition expansion and differential liberation tests were conducted on viscous oil samples. Experiment results for phase behavior and reservoir fluid properties were used to tune the Peng-Robinson equation of state and predict the phase behavior accurately. A comprehensive literature search was carried out to compile available compositional viscosity models and their modifications, for application to heavy or viscous oils. With the help of meticulously amassed new medium-heavy oil viscosity data from experiments, a comparative study was conducted to evaluate the potential of various models. The widely used corresponding state viscosity model predictions deteriorate when applied to heavy oil systems. Hence, a semi-empirical approach (the Lindeloff model) was adopted for modeling the viscosity behavior. Based on the analysis, appropriate adjustments have been suggested: the major one is the division of the pressure-viscosity profile into three distinct regions. New modifications have improved the overall fit, including the saturated viscosities at low pressures. However, with the limited

Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 2001]. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds [NRC, 2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path [Twomey, 1977] and the "semi-direct" effect on cloud coverage [e.g., Ackerman et al ., 2001]." Enhanced aerosol concentrations can also suppress warm rain processes by producing a narrow droplet spectrum that inhibits collision and coalescence processes [e.g., Squires and Twomey, 1961; Warner and Twomey, 1967; Warner, 1968; Rosenfeld, 19991. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect [Albrecht, 1989], is even more complex, especially for mixed-phase convective clouds. Table 1 summarizes the key observational studies identifying the microphysical properties, cloud characteristics, thermodynamics and dynamics associated with cloud systems from high-aerosol continental environments. For example, atmospheric aerosol concentrations can influence cloud droplet size distributions, warm-rain process, cold-rain process, cloud-top height, the depth of the mixed phase region, and occurrence of lightning. In addition, high aerosol concentrations in urban environments could affect precipitation variability by providing an enhanced source of cloud condensation nuclei (CCN). Hypotheses have been developed to explain the effect of urban regions on convection and precipitation [van den Heever and Cotton, 2007 and Shepherd, 2005

Simulated experiments coupled with ocean biota dynamics were performed in laboratory. In these experiments, effects of heavy metal (copper and cadmium) coupled with Ulca pertusa on marine inorganic carbon system and CO2 fluxes were investigated. The results indicated that concentration changes (delta) of components in carbon dioxide system with time scale were correlated with the concentrations and kinds of heavy metal. In copper groups and cadmium groups (0.1 micromol x L(-1) and 1 micromol x L(-1)), DIC HCO3- and PCO2 significantly decreased comparing to the control experiment data( p = 0.01). However, when the heavy metal infusions were higher than the "critical concentration", the above mentioned parameters increased with time scale and their increments followed the uptrend with increasing heavy metal concentrations. The "critical concentration" in copper groups was much lower than that in cadmium groups, which attributed to the tolerance diversity of Ulca pertusa to copper and cadmium. Furthermore, CO2 fluxes under the influences of heavy metal were also regularly changed with time. Sea waters with low infusions of heavy metal represented as sinks to the atmosphere CO2. These sinks would probably convert into CO2 sources after a period of time. Sea waters with comparatively high amount of heavy metal were always to be CO2 sources, and their release fluxes of CO2 augmented along with the increasing infusions of heavy metal. PMID:17304838

As we move from the TRMM to GPM era, more emphasis will be placed on a larger regime of precipitation in mid- and high-latitudes, including light rain, mixed-phase precipitation and snowfall. In these areas, a large and highly variable portion of the total annual precipitation is snow. There is a wealth of observational evidence of brightness temperature depression from frozen hydrometeor scattering at the high frequency from aircraft and spacecraft microwave instruments. Research on the development of snowfall retrieval over land has become increasing important in the last few years (Chen and Staelin, 2003; Kongoli et al., 2004; Skofronick-Jackson et al., 2004, Noh et al., 2006; Aonashi et al., 2007; Liu, 2008; Grecu and Olson, 2008; Kim et al., 2008). However, there is still a considerable amount of work that needs to be done to develop global snowfall detection and retrieval algorithms. This paper describes the development and testing of snowfall models and retrieval algorithms using WRF snowfall simulations and high frequency radiative transfer models for snowfall events took place in January 2007 over Ontario, Canada.

Global Circulation Models (GCMs) are tools of primary importance to obtain future climate projections under different anthropogenic forcing scenarios. However, the GCM coarse resolution (generally few hundred kilometres) it is not suitable to analyse the projections at regional scale (generally few tens kilometres). Usually the gap between the coarse resolution GCMs and the appropriate scale for regional climate studies is bridged by means of dynamical and/or statistical downscaling techniques. The dynamical downscaling approach is based on high-resolution Regional Climate Models (RCM) -- with typical resolutions of tens of kilometres -- driven by GCMs within a limited domain. The RCMs explicitly solve mesoscale atmospheric processes and provide spatially coherent and, to a certain degree, physically consistent output. However, they have in general considerable biases and therefore often cannot directly be used as input for impact models but they must be corrected/calibrated. In this work, of preliminary nature, we focus on precipitation, a key variable for many impact sectors (agriculture, hydrology, etc.) which has a large uncertainty in RCMs and we describe a simple strategy to develop high-resolution precipitation projections over the Great Alpine Region (GAR) combining dynamical downscaling and statistical methods. Specifically, we compare three different bias correction methods to refine the precipitationsimulated by the RegCM4 model and we assess the strengths and limitations of this approach in terms of its robust applicability for climate change studies.

This paper and poster presented a description of the current real-time SPoRT-LIS run over the southeastern CONUS to provide high-resolution, land surface initialization grids for local numerical model forecasts at NWS forecast offices. The LIS hourly output also offers a supplemental dataset to aid in situational awareness for convective initiation forecasts, assessing flood potential, and monitoring drought at fine scales. It is a goal of SPoRT and several NWS forecast offices to expand the LIS to an entire CONUS domain, so that LIS output can be utilized by NWS Western Region offices, among others. To make this expansion cleanly so as to provide high-quality land surface output, SPoRT tested new precipitation datasets in LIS as an alternative forcing dataset to the current radar+gauge Stage IV product. Similar to the Stage IV product, the NMQ product showed comparable patterns of precipitation and soil moisture distribution, but suffered from radar gaps in the intermountain West, and incorrectly set values to zero instead of missing in the data-void regions of Mexico and Canada. The other dataset tested was the next-generation GOES-R QPE algorithm, which experienced a high bias in both coverage and intensity of accumulated precipitation relative to the control (NLDAS2), Stage IV, and NMQ simulations. The resulting root zone soil moisture was substantially higher in most areas.

Climate models have difficulties in correctly simulating clouds and precipitation. It is critical to know the internal structure of clouds and precipitation since it is the vertical distribution of condensate that determines the characteristics of the cloud radiative forcing and lends insight into the vertical structure of condensation heating, which have large impact on the evolution of cloud systems. Cloudsat and CALIPSO provide the unprecedented data that allow us to look at detailed cloud and precipitation structures. In this study, we examine the vertical distribution of clouds and precipitation in CAM5 using simulated CloudSat radar reflectivities. Our focus is to evaluate how well the model simulated clouds over several different important cloud regimes and estimate the effects of simulator uncertainties from precipitation sub-column distribution. The selected regimes include TWP, Southern Ocean, and Australian stratus region. The impacts of different assumptions used to assign precipitation to sub-columns are examined, and the uncertainties from precipitation distribution are analyzed. This work was performed under the auspices of the U. S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344.

The longitudinal instability has potentially disastrous effects on the ion beams used for heavy ion driven inertial confinement fusion. This instability is a {open_quotes}resistive wall{close_quotes} instability with the impedance coining from the induction modules in the accelerator used as a driver. This instability can greatly amplify perturbations launched from the beam head and can prevent focusing of the beam onto the small spot necessary for fusion. This instability has been studied using the WARPrz particle-in-cell code. WARPrz is a 2 1/2 dimensional electrostatic axisymmetric code. This code includes a model for the impedance of the induction modules. Simulations with resistances similar to that expected in a driver show moderate amounts of growth from the instability as a perturbation travels from beam head to tail as predicted by cold beam fluid theory. The perturbation reflects off the beam tail and decays as it travels toward the beam head. Nonlinear effects cause the perturbation to steepen during reflection. Including the capacitive component of the, module impedance. has a partially stabilizing effect on the longitudinal instability. This reduction in the growth rate is seen in both cold beam fluid theory and in simulations with WARPrz. Instability growth rates for warm beams measured from WARPrz are lower than cold beam fluid theory predicts. Longitudinal thermal spread cannot account for this decrease in the growth rate. A mechanism for coupling the transverse thermal spread to decay of the longitudinal waves is presented. The longitudinal instability is no longer a threat to the heavy ion fusion program. The simulations in this thesis have shown that the growth rate for this instability will not be as large as earlier calculations predicted.

Variant selection of alpha phase during its precipitation from beta matrix plays a key role in determining transformation texture and final mechanical properties of alpha/beta and beta titanium alloys. In this study we develop a three-dimensional quantitative phase field model (PFM) to predict variant selection and microstructure evolution during beta to alpha transformation in polycrystalline Ti-6Al-4V under the influence of different processing variables. The model links its inputs directly to thermodynamic and mobility databases, and incorporates crystallography of BCC to HCP transformation, elastic anisotropy, defects within semi-coherent alpha/beta interfaces and elastic inhomogeneities among different beta grains. In particular, microstructure and transformation texture evolution are treated simultaneously via orientation distribution function (ODF) modeling of alpha/beta two-phase microstructure in beta polycrystalline obtained by PFM. It is found that, for a given undercooling, the development of transformation texture of the alpha phase due to variant selection during precipitation depends on both externally applied stress or strain, initial texture state of parent beta sample and internal stress generated by the precipitation reaction itself. Moreover, the growth of pre-existing widmanstatten alpha precipitates is accompanied by selective nucleation and growth of secondary alpha plates of preferred variants. We further develop a crystallographic model based on the ideal Burgers orientation relationship (BOR) between GBalpha and one of the two adjacent beta grains to investigate how a prior beta grain boundary contributes to variant selection of grain boundary allotriomorph (GBalpha). The model is able to predict all possible special beta grain boundaries where GBalpha is able to maintain BOR with two neighboring grain. In particular, the model has been used to evaluate the validity of all current empirical variant selection rules to obtain more insight of

Using parallel three-dimensional Monte Carlo simulations, we investigated the effects of precipitates and sub-boundaries on abnormal grain growth (AGG) of Goss grains based on real orientation data of primary recrystallized Fe-3%Si steel. The simulations showed that AGG occurred in the presence of precipitates which inhibited the grain growth of matrix grains, whereas it did not in the absence of precipitates. The role of precipitates in enhancing AGG is to maintain a relatively high fraction of high energy boundaries between matrix grains, which increases the probability of sub-boundary-enhanced solid-state wetting of an abnormally growing grain. The microstructure evolved by the simulation could reproduce many realistic features of abnormally growing grains, such as the formation of island and peninsular grains and merging of abnormally growing grains which appeared to be separated initially on the cross-section.

In this study we investigate possible changes in temperature and precipitation on a regional scale over Europe from 1961 to 2100. We use data from two ensembles of climate simulations, one global and one regional, over the Europe-CORDEX domain. The global ensemble includes nine coupled atmosphere ocean general circulation models (AOGCMs) from the CMIP5 project with horizontal resolution varying from about 1° to 3°, namely CanESM2, CNRM-CM5, HadGEM2-ES, IPSL-CM5A-MR, NorESM1-M, EC-EARTH, MIROC5, GFDL-ESM2M and MPI-ESM-LR. In the regional ensemble all 9 AOGCMs are downscaled at the Rossby Centre (SMHI) by a regional climate model - RCA4 at 0.44° resolution. Two forcing scenarios are considered, RCP 4.5 and 8.5. The experimental setup allows us to illustrate how uncertainties in future climate change are related to forcing scenario and to forcing AOGCM at different time periods. Further, we investigate the benefit of the higher horizontal resolution, in RCA4 by comparing the results to the coarser driving AOGCM data. The significance of the results is investigated by comparing to i) the model simulated natural variability, and, ii) the biases in the control period. Results dealing with changes in the seasonal cycle of temperature and precipitation and their relation to changes in the large-scale atmospheric circulation are presented. We also address higher-order variability by showing results for changes in temperature extremes and for changes in intensity and frequency of extreme precipitation.

A wide variety of organic compounds have been detected in such extraterrestrial bodies as meteorites and comets Amino acids were identified in the extracts from Murchison meteorite and other carbonaceous chondrites It is hypothesized that these compounds are originally formed in ice mantles of interstellar dusts ISDs in molecular clouds by cosmic rays and ultraviolet light UV Formation of amino acid precursors by high energy protons or UV irradiation of simulated ISDs was reported by several groups The amino acid precursors were however not well-characterized We irradiated a frozen mixture of methanol ammonia and water with heavy ions to study possible organic compounds abiotically formed in molecular clouds by cosmic rays A mixture of methanol ammonia and water was irradiated with carbon beams 290 MeV u from a heavy ion accelerator HIMAC of National Institute of Radiological Sciences Japan Irradiation was performed either at room temperature liquid phase or at 77 K solid phase The products were characterized by gel filtration chromatography GFC FT-IR pyrolysis PY -GC MS etc Amino acids were analyzed by HPLC and GC MS after acid hydrolysis or the products Amino acids such as glycine and alanine were identified in the products in both the cases of liquid phase and solid phase irradiation Energy yields G-values of glycine were 0 014 liquid phase and 0 007 solid phase respectively Average molecular weights of the products were estimated as to 2300 in both the case Aromatic hydrocarbons N-containing heterocyclic

A 3-D Monte Carlo energetic particle transport model has been developed and successfully applied to ion precipitation into planetary upper atmospheres in our solar system (viz., Earth, Mars, Jupiter, and Saturn), and can be readily be extended using a full Lorentz motion formu-lation in the absence of strong dipole planetary magnetic fields. This model can be used with a variety of other models to assess the influence of hot ion precipitation on the thermosphere and exosphere of planetary atmospheres and the subsequent sputtering and escape. For instance in the case of Mars, a pick-up ion transport model already exists to allow for particle acceleration exerted by the convection electric field used in conjunction with existing model results from the Mars Thermosphere General Circulation Model (MTGCM) and the BATS-R-US global MHD model. The loss of exospheric neutrals through ionization, in which they become pick-up ions in the solar wind, can be calculated to examine the relative contribution of the various ionization processes. Solar wind protons as well as pick-up ions from a planetary exosphere routinely enter and alter their upper atmosphere. A study of the pick-up ion escape, sputtering, ion-ization, excitation, and energy deposition will be reviewed and discussed, resulting in a robust examination of the influence of energetic ion transport on planetary upper atmospheres.

A two-dimensional model of magnetosphere-ionosphere coupling is presented. It includes Alfvén wave dynamics, ion motion along the geomagnetic field, chemical reactions between ions and neutrals, collisions between different species, and a parametric model of electron precipitation. Representative simulations are presented, along with a discussion of the physical mechanisms that are important in forming oxygen ion field-aligned plasma flows. In particular, it is demonstrated that ion upwelling is strongly affected by the ponderomotive force of standing Alfvén waves in the ionospheric Alfvén resonator, and by enhanced electric fields that are produced when electrons are heated by soft electron precipitation. It is verified that the simulations are in qualitative agreement with available theoretical predictions. In the resonator, in addition to the ponderomotive force, a contribution to the upflow comes from centrifugal acceleration. Heating by the current of standing waves increases parallel electric fields and ion pressure gradients only at low altitudes where they are easily balanced by friction with neutrals. This prevents development of fast field-aligned ion flows in the E-layer and lower F-layer.

RAON (Rare isotope Accelerator Of Newness) heavy ion accelerator of the rare isotope science project in Daejeon, Korea, has been designed to accelerate multiple-charge-state beams to be used for various science programs. In the RAON accelerator, the rare isotope beams which are generated by an isotope separation on-line system with a wide range of nuclei and charges will be transported through the post Low Energy Beam Transport (LEBT) section to the Radio Frequency Quadrupole (RFQ). In order to transport many kinds of rare isotope beams stably to the RFQ, the post LEBT should be devised to satisfy the requirement of the RFQ at the end of post LEBT, simultaneously with the twiss parameters small. We will present the recent lattice design of the post LEBT in the RAON accelerator and the results of the beam dynamics simulations from it. In addition, the error analysis and correction in the post LEBT will be also described.

A nonlinear, multibody, six-degrees-of-freedom digital simulation has been developed to study generic Heavy Lift Airship (HLA) dynamics and control. The basic aerodynamic functions developed to model the hull, tail, and rotor loads continuously over all incidence ranges are reviewed and applied to a Quadrotor HLA with a low fineness ratio hull and a small vee-tail. Trim calculations for a test vehicle suggest control power deficiencies in crosswind stationkeeping for the unloaded vehicle. Gust responses show the importance of correctly calculating loads due to accelerated relative motion of air and hull. Numerically linearized dynamics for the test vehicle show the existence of a divergent yaw mode, and an oscillatory pitch mode whose stability characteristics are sensitive to flight speed. A considerable improvement in the vehicle's stability and response results from a simple multi-axis closed-loop control system operating on the rotors and propeller blades.

Capabilities and accuracy issues in Lagrangian tracking of heavy particles in velocity fields obtained from large-eddy simulations (LES) of wall-bounded turbulent flows are reviewed. In particular, it is shown that, if no subgrid scale (SGS) model is added to the particle motion equations, particle preferential concentration and near-wall accumulation are significantly underestimated. Results obtained with SGS modeling for the particle motion equations based on approximate deconvolution are briefly recalled. Then, the error purely due to filtering in particle tracking in LES flow fields is singled out and analyzed. The statistical properties of filtering errors are characterized in turbulent channel flow both from an Eulerian and a Lagrangian viewpoint. Implications for stochastic SGS modeling in particle motion equations are briefly outlined.

Soil samples from three watersheds of New York State were treated with simulated rain at pH 3.5, 4.1, and 5.6 daily for 14 d, at 12 3-d intervals in three separate tests, or at 22 7-d intervals. Except for one system of treating the three forest soils, simulated acid rain reduced the amount of organic matter leached from samples of soil from which more than 0.05% of the organic carbon was leached during the exposure period. In the soil samples representing the exceptions, acid rain enhanced the leaching of organic matter. Samples from the organic layer of the treated samples of acid soil were taken at two equal depths, and the rates of organic matter decomposition in the two layers were studied. As compared with simulated rain at pH 5.6, simulated acid rain reduced the decomposition of organic matter in the three soils at both depths in three of the five tests and at both depths of two of the soils in the fourth test. In some instances, organic matter decomposition was enhanced by the simulated acid rain. Except for the sample of soil at the highest initial pH, carbon mineralization was inhibited in soils and treatments in which simulated acid rain reduced the amount of organic carbon leached, and it was stimulated in soils and treatments in which the quantity of organic carbon leached was increased by the simulated acid rain. 12 references, 3 figures, 8 tables.

A search for heavy Majorana neutrinos is performed using an event signature defined by two same-sign muons accompanied by two jets. This search is an extension of previous searches, (L3, DELPHI, CMS, ATLAS), using 19.7 fb -1 of data from the 2012 Large Hadron Collider experimental run collected by the Compact Muon Solenoid experiment. A mass window of 40-500 GeV/ c2 is explored. No excess events above Standard Model backgrounds is observed, and limits are set on the mixing element squared, |VmuN|2, as a function of Majorana neutFnrino mass. The Hadronic Forward (HF) Detector's performance will degrade as a function of the number of particles delivered to the detector over time, a quantity referred to as integrated luminosity and measured in inverse femtobarns (fb-1). In order to better plan detector upgrades, the CMS Forward Calorimetry Task Force (FCAL) group and the CMS Hadronic Calorimeter (HCAL) group have requested that radiation damage be simulated and the subsequent performance of the HF subdetector be studied. The simulation was implemented into both the CMS FastSim and CMS FullSim simulation packages. Standard calorimetry performance metrics were computed and are reported. The HF detector can expect to perform well through the planned delivery of 3000 fb-1.

We present simulated detections of O+, O2+ and CO2+ ions at Mars along a virtual orbit in the Mars space environment. Planetary pick-up ions are formed through the direct interaction of the solar wind with the neutral upper atmosphere, causing the newly created ions to be picked up and accelerated by the background convective electric field. Because previous missions such as Mars Global Surveyor (MGS) and Mars Express (MEX) have not been able to measure the interplanetary magnetic field (IMF) components simultaneously with plasma measurements, the response of heavy planetary pick-up ions to changes in the IMF has not been well characterized. Using a steady-state multi-species MHD model to provide the background electric and magnetic fields, the Mars Test Particle (MTP) simulation can trace each of these particles along field lines in near-Mars space and construct virtual ion detections from a spacecraft orbit. Specifically, we will present energy-time spectrograms and velocity space distributions (VSDs) for a selection of orbits during different IMF configurations and solar cycle conditions. These simulated orbits have broader implications for how to measure ion escape. Using individual particle traces, the origin and trajectories of different ion populations can be analyzed in order to assess how and where they contribute to the total atmospheric escape rate, which is a major objective of the upcoming MAVEN mission.

Realistically simulating convective and stratiform structures of mesoscale convective systems (MCSs) requires proper representation of the large-scale environment and adequate representation of convective dynamics and parameterized microphysics in the simulation. The partitioning and areal coverage of such structures determine the heating distribution of any given system, thus affecting the large-scale dynamic response to the system. This issue is becoming evermore relevant with increasing computing power that will allow numerical weather prediction and global climate models to approach 1-10 km horizontal grid spacing in the coming decades. To test whether mesoscale simulations using 1-km grid spacing properly simulate a large tropical monsoonal MCS, several cloud-resolving model (CRM) and limited area model (LAM) simulations of a Tropical Warm Pool-International Cloud Experiment (TWP-ICE) MCS are compared with several observational retrievals. These comparisons expose a high bias in convective radar reflectivity aloft and a low bias in stratiform rainfall. Combined with errors due to large-scale environmental biases, model setup, and bulk microphysics parameterization assumptions, these biases appear related to overly intense deep convection in the simulations based on comparisons with dual-Doppler retrieved vertical velocity. The difference between simulated and dual-Doppler retrieved vertical velocity is especially large in the upper troposphere. This upper tropospheric difference is partially due to lofting and freezing of large rain water contents in simulations, which leads to large increases in buoyancy through latent heating. Possible reasons for overly intense simulated convective updrafts with large condensate loadings at mid and upper levels are explored.

Heavy ion fusion requires injection, transport and acceleration of high current beams. Detailed simulation of such beams requires fully self-consistent space charge fields and three dimensions. WARP3D, developed for this purpose, is a particle-in-cell plasma simulation code optimized to work within the framework of an accelerator`s lattice of accelerating, focusing, and bending elements. The code has been used to study several test problems and for simulations and design of experiments. Two applications are drift compression experiments on the MBE-4 facility at LBL and design of the electrostatic quadrupole injector for the proposed ILSE facility. With aggressive drift compression on MBE-4, anomalous emittance growth was observed. Simulations carried out to examine possible causes showed that essentially all the emittance growth is result of external forces on the beam and not of internal beam space-charge fields. Dominant external forces are the dodecapole component of focusing fields, the image forces on the surrounding pipe and conductors, and the octopole fields that result from the structure of the quadrupole focusing elements. Goal of the design of the electrostatic quadrupole injector is to produce a beam of as low emittance as possible. The simulations show that the dominant effects that increase the emittance are the nonlinear octopole fields and the energy effect (fields in the axial direction that are off-axis). Injectors were designed that minimized the beam envelope in order to reduce the effect of the nonlinear fields. Alterations to the quadrupole structure that reduce the nonlinear fields further were examined. Comparisons were done with a scaled experiment resulted in very good agreement.

We present laboratory experiments aiming to understand the processes affecting the δ13C and δ18O values of speleothems during precipitation of calcite from a thin layer of solution. In particular, we determined the precipitation rates and the isotope fractionation factors in dependence of several parameters, such as temperature, cave pCO2 and supersaturation with respect to calcite. The experiments were performed in a climate box in order to simulate cave conditions and to control them during the experiments[1]. In the experiments, a thin film of a CaCO3-CO2-H2O-solution supersaturated with respect to calcite flew down an inclined marble surface or a sand-blasted borosilicate glass plate, and the drip water was sampled at different distances and, thus, residence times on the plate. Subsequently, pH, electrical conductivity and the δ13C and δ18O values of the dissolved inorganic carbon (DIC) as well as the precipitated CaCO3 were determined. In addition, we determined the stable isotope values of the drip water and the atmosphere inside the box during the experiments. This enabled the identification of carbon and oxygen isotope fractionation factors between all carbonate species. The experiments were conducted at 10, 20 and 30 ° C, a pCO2 of 1000 and 3000 ppmV and with a Ca2+ concentration of 2 and 5 mmol/l. We observed an exponential decay of conductivity with increasing distance of flow documenting progressive precipitation of calcite confirming previous observations[2]. The corresponding time constants of precipitation range from 180 to 660 s. Both the δ13C and δ18O values show a progressive increase along the flow path. The enrichment of the δ13C values seems to be strongly influenced by kinetic isotope fractionation, whereas the δ18O values are in the range of isotopic equilibrium. The fractionation between the precipitated CaCO3 and DIC is between -1 and - 6.5 ‰ for carbon isotopes (13ɛ) and between -1.5 and -3 ‰ for oxygen isotopes (18ɛ). The

Despite its importance in numerous industrial and natural processes, many unsolved questions remain regarding the mechanism of silica precipitation in aqueous solutions: order of the reaction, role of silica oligomers, existence of an induction time and characteristics of the particle population. Beyond empirical approaches used in the past, we demonstrate that the classical nucleation theory associated to a size dependent growth law, as embedded in the NANOKIN code (1-3), allows a quantitative description of precipitation occurring under largely different experimental conditions : preexisting initial supersaturation in a large domain of temperature (5-150°C) and chemical composition (4), supersaturation reached by neutralization of a high pH silica solution (5) or by fast cooling (6). In that way, the mechanism of silica precipitation can be unraveled. We are able to discard the hypothesis of an induction time as an explanation for the plateaus observed in the saturation curves in these experiments. We challenge the role of oligomer incorporation at the growth stage to account for the observed rate laws and we stress the difference between the order of the growth law and the order of the total reaction rate. We also demonstrate that the characteristics of the particle population are strongly dependent on the way supersaturation is reached (7). Such a microscopic approach thus proves to be well suited to elucidate the mechanism of nanoparticle formation in natural and industrial contexts, involving silica, but also other mineral phases produced as nanoparticles (8). (1) Noguera C., Fritz B., Clément A. and Barronet A., J. Cryst. Growth, 2006, 297, 180. (2) Noguera C., Fritz B., Clément A. and Barronet A., J. Cryst. Growth, 2006, 297, 187. (3) Fritz B., Clément A., Amal Y. and Noguera C., Geochim. Cosmochim. Acta, 2009, 73, 1340. (4) Rothbaum, H.P. and Rohde A.G., J. Colloid Interf. Sci., 1979,71, 533. (5) Tobler D.J., Shaw S. and Benning L.G., Geochim

The purpose of this study is to investigate the applicability of distributed basin-scale runoff modeling, driven by rainfall data from either ground-based observations or mesoscale simulations, in response to typhoons invading Taiwan. Typhoons Herb (1996) and Zeb (1998) were selected for calibrating the runoff parameters reflecting the landuse conditions in the basin and evaluating the applicability of observed and simulated rainfall data toward runoff estimations, respectively. Upstream basins of Reservoir Shihmen with a drainage area of 764 km2 and Reservoir Feitsui with a drainage area of 303 km2 were the domains of interest in this preliminary study. Ground-based observations of both stream flows and station rainfalls were collected in an hourly resolution. The mesoscale model,MM5, simulation for Herb was conducted in 4-nested grids with the finest resolution of 2.2 km and 2-nested grids with the finest resolution of 15 km for Zeb, and the time resolution for both cases was 5 minutes. Accumulated total rain was accommodated with terrain elevation in MM5 simulations and station data to provide areal rainfall distributions. While the ground-based observations were sparse and incapable of correctly representing areal rainfall characteristics, the MM5 simulated data may introduce great uncertainties in basin-scale hydrological applications. The experience learned from this study is expected to provide an applicable approach with both ground-based observations and mesoscale simulations in basin-scale runoff computations.

The first results of a regional circulation model REMOiso fitted with water isotope diagnostics are compared with various isotope series from central Europe. A 2 year case study is conducted from March 1997 to February 1999 centred over Europe, analysing daily and monthly measurements. Isotope signals over Europe are dominated by the typical isotopic effects such as temperature, continental and altitude effects, both on annual and seasonal scales. These well-known isotopic effects are successfully reproduced by REMOiso, using two different boundary data sets. In a first simulation, the European Centre for Medium-range Weather Forecasts (ECMWF) analyses serve as boundary conditions, where water isotopes were parameterized by a simple temperature dependence. In a second simulation, boundary conditions both for climatic and isotopic variables are taken from the ECHAMiso general circulation model output. The comparison of both simulations shows a very high sensitivity of the simulated 18O signal to boundary conditions. The ECMWF-nested simulation shows an average offset of -4.5 in mean 18O values and exaggerated seasonal amplitude. The ECHAM-nested simulation represents correctly the observed mean 18O values, although with a dampened seasonality. REMOiso's isotope module is further validated against daily 18O measurements at selected stations (Nordeney, Arkona and Hohenpeissenberg) situated in Germany. Copyright

Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low clean concentration and a high dirty concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large eddy model applying warm-rain bin microphysics. Simulations with and without collision-coalescence are considered with cloud condensation nuclei (CCN) concentrations of 30, 60, 120, and 240 mg-1. Simulations with collision-coalescence include either the standard gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts model results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the effects of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. Model results show a systematic shift in the cloud-top height distributions, with an increasing contribution of deeper clouds for stronger precipitating cases. We show that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013); namely, the increase of drizzle/rain leads to a more efficient condensate offloading in the upper parts of the cloud field. A second effect involves suppression of the cloud droplet evaporation near cloud edges in low-CCN simulations, as documented in previous studies (e.g., Xue and Feingold, 2006). We pose the question whether the effects of cloud turbulence on drizzle/rain formation in shallow cumuli can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of

Through explicitly resolved cloud-scale processes by embedded 2-D cloud-resolving models (CRMs), the Multiscale Modeling Framework (MMF) known as the superparameterization has been reasonably successful to simulate various atmospheric events over a wide range of time scales. One thing to be justified is, however, if the influence of complex 3-D topography can be adequately represented by the embedded 2-D CRMs. In this study, simulations are performed in the presence of a variety of topography with embedded 3-D and 2-D CRMs in a single-column inactive GCM. Through the comparison between these simulations, it is demonstrated that the 2-D representation of topography is able to simulate the statistics of precipitation due to 3-D topography reasonably well as long as the topographic characteristics, such as the mean and standard deviation, are closely recognized. It is also shown that the use of two perpendicular sets of 2-D representations tends to reduce the error due to a 2-D representation.

The description of the hydrological cycle in Atmospheric General Circulation Models (GCMs) can be validated using water isotopes as tracers. Many GCMs now simulate the movement of the stable isotopes of water, but here we present the first GCM simulations modelling the content of natural tritium in water. These simulations were obtained using a version of the LMDZ General Circulation Model enhanced by water isotopes diagnostics, LMDZ-iso. To avoid tritium generated by nuclear bomb testing, the simulations have been evaluated against a compilation of published tritium datasets dating from before 1950, or measured recently. LMDZ-iso correctly captures the observed tritium enrichment in precipitation as oceanic air moves inland (the so-called continental effect) and the observed north-south variations due to the latitudinal dependency of the cosmogenic tritium production rate. The seasonal variability, linked to the stratospheric intrusions of air masses with higher tritium content into the troposphere, is correctly reproduced for Antarctica with a maximum in winter. LMDZ-iso reproduces the spring maximum of tritium over Europe, but underestimates it and produces a peak in winter that is not apparent in the data. This implementation of tritium in a GCM promises to provide a better constraint on: (1) the intrusions and transport of air masses from the stratosphere, and (2) the dynamics of the modelled water cycle. The method complements the existing approach of using stable water isotopes.

Extreme rainfall events in the central Indian region are often related to the passage of synoptic scale monsoon low-pressure systems (LPS). This study uses the surrogate climate change method on ten monsoon LPS cases connected to observed extreme rainfall events, to investigate how sensitive the precipitation and runoff are to an idealized warmer and moister atmosphere. The ten cases are simulated with three different initial and lateral boundary conditions: the unperturbed control run, and two sets of perturbed runs where the atmospheric temperature is increased uniformly throughout the atmosphere, the specific humidity increased according to Clausius Clapeyron's relation, but the large-scale flow is unchanged. The difference between the control and perturbed simulations are mainly due to the imposed warming and feedback influencing the synoptic flow. The mean precipitation change with warming in the central Indian region is 18-20 %/K, with largest changes at the end of the LPS tracks. The LPS in the warmer runs are bringing more moisture further inland that is released as precipitation. In the perturbed runs the precipitation rate is increasing at all percentiles, and there is more frequent rainfall with very heavy intensities. This leads to a shift in which category that contributes most to the total precipitation: more of the precipitation is coming from the category with very heavy intensities. The runoff changes are similar to the precipitation changes, except the response in intensity of very heavy runoff, which is around twice the change in intensity of very heavyprecipitation.

Extreme rainfall events in the central Indian region are often related to the passage of synoptic scale monsoon low-pressure systems (LPS). This study uses the surrogate climate change method on ten monsoon LPS cases connected to observed extreme rainfall events, to investigate how sensitive the precipitation and runoff are to an idealized warmer and moister atmosphere. The ten cases are simulated with three different initial and lateral boundary conditions: the unperturbed control run, and two sets of perturbed runs where the atmospheric temperature is increased uniformly throughout the atmosphere, the specific humidity increased according to Clausius Clapeyron's relation, but the large-scale flow is unchanged. The difference between the control and perturbed simulations are mainly due to the imposed warming and feedback influencing the synoptic flow. The mean precipitation change with warming in the central Indian region is 18-20 %/K, with largest changes at the end of the LPS tracks. The LPS in the warmer runs are bringing more moisture further inland that is released as precipitation. In the perturbed runs the precipitation rate is increasing at all percentiles, and there is more frequent rainfall with very heavy intensities. This leads to a shift in which category that contributes most to the total precipitation: more of the precipitation is coming from the category with very heavy intensities. The runoff changes are similar to the precipitation changes, except the response in intensity of very heavy runoff, which is around twice the change in intensity of very heavyprecipitation.

Global-to-regional surface temperature and precipitation trends are examined based on the CMIP5 model 100 years of historical simulations and another future 100 years following the Representative Concentration Pathway (RCP) emission scenario projection. Different from the ensemble mean approach in the previous studies, the probabilistic multimodal ensemble prediction with Gaussian fitting is used to generate probabilistic simulations. The results show that the averaged precipitation increases slightly with global warming, but the response is not globally uniform. Both historical model simulations and the RCP emission scenario projections suffer from large uncertainties in the selected models and the geographic distribution. The spatial distribution of spreads among the multimodal scenario projections is similar to that in the historical simulations, except the magnitude of spread sharply increases and the region expands equatorward and poleward in surface temperature and precipitation, respectively.

Results of a study using a rainfall simulator to define infiltration parameters for use in watershed modeling are presented. A total of 23 rainfall-simulation runs were made on five small plots representing four representative soil-vegetation types of the study watershed in eastern Colorado. Data for three observed rainfall-runoff events were recorded by gages on four of the plots. Data from all events were used to develop best-fit parameters of the Green and Ampt infiltration equation. The hydraulic conductivity of the transmission zone, KSAT, grossly controlled the goodness of fit of all modeling attempts. Results of fitting KSAT to reproduce runoff from rainfall simulator runs and results of fitting KSAT to reproduce runoff from observed rainfall-runoff events are inconsistent. Variations in results from site to site and at different times of the year were observed. (USGS)

Abstract Despite its fundamental role in driving the genesis and evolution of tropical cyclones as well as large scale atmospheric waves including ENSO, monsoon and MJO, the spatial and temporal distribution of latent heating (LH) remains one of the largest uncertainties in weather and climate modeling. With the rapid advance in satellite active sensors such as the TRMM PR, CloudSat CPR and the coming GPM DPR, more comprehensive and reliable observations of cloud and precipitation profiles provide great opportunities to improve the accuracy of estimating LH from space. However, LH is released through the 'processes' of water phase change in the atmosphere while satellite observations provide the estimation of the 'state' of cloud and precipitation, the physical linkages between LH to cloud and precipitation profiles are required to develop next generation physical-based LH algorithms. In this study, we examined the relationships among the condensations heating (LHcon), cloud water content (CWC) and rain rate (Rr) in the Weather Research and Forecasting (WRF) model simulations of typhoon Chaba (2004) under five different microphysical schemes including Purdue Lin, Goddard Cumulus Ensemble Model, WSM6, Thompson et al. and Morrison et al. 2-Moment schemes, respectively. Firstly, the LHcon has the highest correlations (~ 0.85 for convective rains) with the term of Rr αCWC which represents the rate of rain formation from auto-conversion and accretion. Although cloud and precipitation, as the ultimate outcomes of water vapor condensation process, also have inherent correlations to LHcon, the connections are significantly weaker than the LHcon - Rr αCWC linkages. Such findings are valid in all selected microphysical schemes in both 2-D CRM (Min et al 2013; Li et al 2013) and 3-D WRF simulations. Secondly, the sensitivity of maximum explained variances of LHcon by Rr αCWC to different microphysical schemes are relatively low. The associated optimal exponential of α is

The space-charge-dominated beams in a heavy ion beam driven inertial fusion (HIF) accelerator must be focused onto small (few mm) spots at the fusion target, and so preservation of a small emittance is crucial. The nonlinear beam self-fields can lead to emittance growth; thus, a self-consistent field description is necessary. We have developed a multi-dimensional time-dependent discrete particle simulation code, WARP, and are using it to study the behavior of HIF beams. The code's 3d package combines features of an accelerator code and a particle-in-cell (PIC) plasma simulation. Novel techniques allow it to follow beams through many accelerator elements over long distances and around bends. We have used the code to understand the emittance growth observed in the MBE4 experiment at Lawrence Berkeley Laboratory (LBL) under conditions of aggressive drift-compression. We are currently applying it to LBL's planned ILSE experiments, and (most recently) to an ESQ injector option being evaluated for ILSE. The code's r, z package is being used to study the axial confinement afforded by the shaped ends of the accelerating pulses, and to study longitudinal instability induced by induction module impedance.

The steady-state and transient effects of simulatedheavy rain on the subsonic aerodynamic characteristics of a wing model were determined in the Langley 14- by 22-Foot Subsonic Tunnel. The 1.29 foot chord wing was comprised of a NACA 23015 airfoil and had an aspect ratio of 6.10. Data were obtained while test variables of liquid water content, angle of attack, and trailing edge flap angle were parametrically varied at dynamic pressures of 10, 30, and 50 psf (i.e., Reynolds numbers of .76x10(6), 1.31x10(6), and 1.69x10(6)). The experimental results showed reductions in lift and increases in drag when in the simulated rain environment. Accompanying this was a reduction of the stall angle of attack by approximately 4 deg. The transient aerodynamic performance during transition from dry to wet steady-state conditions varied between a linear and a nonlinear transition.